{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Examples and Exercises from Think Stats, 2nd Edition\n",
    "\n",
    "http://thinkstats2.com\n",
    "\n",
    "Copyright 2016 Allen B. Downey\n",
    "\n",
    "MIT License: https://opensource.org/licenses/MIT\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from __future__ import print_function, division\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore', category=FutureWarning)\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import random\n",
    "\n",
    "import thinkstats2\n",
    "import thinkplot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Time series analysis\n",
    "\n",
    "Load the data from \"Price of Weed\"."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>price</th>\n",
       "      <th>amount</th>\n",
       "      <th>quality</th>\n",
       "      <th>date</th>\n",
       "      <th>ppg</th>\n",
       "      <th>state.name</th>\n",
       "      <th>lat</th>\n",
       "      <th>lon</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Annandale</td>\n",
       "      <td>VA</td>\n",
       "      <td>100</td>\n",
       "      <td>7.075</td>\n",
       "      <td>high</td>\n",
       "      <td>2010-09-02</td>\n",
       "      <td>14.13</td>\n",
       "      <td>Virginia</td>\n",
       "      <td>38.830345</td>\n",
       "      <td>-77.213870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Auburn</td>\n",
       "      <td>AL</td>\n",
       "      <td>60</td>\n",
       "      <td>28.300</td>\n",
       "      <td>high</td>\n",
       "      <td>2010-09-02</td>\n",
       "      <td>2.12</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>32.578185</td>\n",
       "      <td>-85.472820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Austin</td>\n",
       "      <td>TX</td>\n",
       "      <td>60</td>\n",
       "      <td>28.300</td>\n",
       "      <td>medium</td>\n",
       "      <td>2010-09-02</td>\n",
       "      <td>2.12</td>\n",
       "      <td>Texas</td>\n",
       "      <td>30.326374</td>\n",
       "      <td>-97.771258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Belleville</td>\n",
       "      <td>IL</td>\n",
       "      <td>400</td>\n",
       "      <td>28.300</td>\n",
       "      <td>high</td>\n",
       "      <td>2010-09-02</td>\n",
       "      <td>14.13</td>\n",
       "      <td>Illinois</td>\n",
       "      <td>38.532311</td>\n",
       "      <td>-89.983521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Boone</td>\n",
       "      <td>NC</td>\n",
       "      <td>55</td>\n",
       "      <td>3.540</td>\n",
       "      <td>high</td>\n",
       "      <td>2010-09-02</td>\n",
       "      <td>15.54</td>\n",
       "      <td>North Carolina</td>\n",
       "      <td>36.217052</td>\n",
       "      <td>-81.687983</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         city state  price  amount quality       date    ppg      state.name  \\\n",
       "0   Annandale    VA    100   7.075    high 2010-09-02  14.13        Virginia   \n",
       "1      Auburn    AL     60  28.300    high 2010-09-02   2.12         Alabama   \n",
       "2      Austin    TX     60  28.300  medium 2010-09-02   2.12           Texas   \n",
       "3  Belleville    IL    400  28.300    high 2010-09-02  14.13        Illinois   \n",
       "4       Boone    NC     55   3.540    high 2010-09-02  15.54  North Carolina   \n",
       "\n",
       "         lat        lon  \n",
       "0  38.830345 -77.213870  \n",
       "1  32.578185 -85.472820  \n",
       "2  30.326374 -97.771258  \n",
       "3  38.532311 -89.983521  \n",
       "4  36.217052 -81.687983  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "transactions = pd.read_csv('mj-clean.csv', parse_dates=[5])\n",
    "transactions.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following function takes a DataFrame of transactions and compute daily averages."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def GroupByDay(transactions, func=np.mean):\n",
    "    \"\"\"Groups transactions by day and compute the daily mean ppg.\n",
    "\n",
    "    transactions: DataFrame of transactions\n",
    "\n",
    "    returns: DataFrame of daily prices\n",
    "    \"\"\"\n",
    "    grouped = transactions[['date', 'ppg']].groupby('date')\n",
    "    daily = grouped.aggregate(func)\n",
    "\n",
    "    daily['date'] = daily.index\n",
    "    start = daily.date[0]\n",
    "    one_year = np.timedelta64(1, 'Y')\n",
    "    daily['years'] = (daily.date - start) / one_year\n",
    "\n",
    "    return daily"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following function returns a map from quality name to a DataFrame of daily averages."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def GroupByQualityAndDay(transactions):\n",
    "    \"\"\"Divides transactions by quality and computes mean daily price.\n",
    "\n",
    "    transaction: DataFrame of transactions\n",
    "    \n",
    "    returns: map from quality to time series of ppg\n",
    "    \"\"\"\n",
    "    groups = transactions.groupby('quality')\n",
    "    dailies = {}\n",
    "    for name, group in groups:\n",
    "        dailies[name] = GroupByDay(group)        \n",
    "\n",
    "    return dailies"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`dailies` is the map from quality name to DataFrame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "dailies = GroupByQualityAndDay(transactions)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following plots the daily average price for each quality."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/downey/anaconda3/envs/ModSimPy/lib/python3.6/site-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.\n",
      "  warnings.warn(message, mplDeprecation, stacklevel=1)\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 576x720 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "thinkplot.PrePlot(rows=3)\n",
    "for i, (name, daily) in enumerate(dailies.items()):\n",
    "    thinkplot.SubPlot(i+1)\n",
    "    title = 'Price per gram ($)' if i == 0 else ''\n",
    "    thinkplot.Config(ylim=[0, 20], title=title)\n",
    "    thinkplot.Scatter(daily.ppg, s=10, label=name)\n",
    "    if i == 2: \n",
    "        plt.xticks(rotation=30)\n",
    "        thinkplot.Config()\n",
    "    else:\n",
    "        thinkplot.Config(xticks=[])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can use `statsmodels` to run a linear model of price as a function of time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import statsmodels.formula.api as smf\n",
    "\n",
    "def RunLinearModel(daily):\n",
    "    model = smf.ols('ppg ~ years', data=daily)\n",
    "    results = model.fit()\n",
    "    return model, results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here's what the results look like."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "high\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>OLS Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>           <td>ppg</td>       <th>  R-squared:         </th> <td>   0.444</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>                   <td>OLS</td>       <th>  Adj. R-squared:    </th> <td>   0.444</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>             <td>Least Squares</td>  <th>  F-statistic:       </th> <td>   989.7</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>             <td>Thu, 24 Jan 2019</td> <th>  Prob (F-statistic):</th> <td>3.69e-160</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                 <td>09:23:26</td>     <th>  Log-Likelihood:    </th> <td> -1510.1</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>No. Observations:</th>      <td>  1241</td>      <th>  AIC:               </th> <td>   3024.</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Residuals:</th>          <td>  1239</td>      <th>  BIC:               </th> <td>   3035.</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Model:</th>              <td>     1</td>      <th>                     </th>     <td> </td>    \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>      <td>nonrobust</td>    <th>                     </th>     <td> </td>    \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "      <td></td>         <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Intercept</th> <td>   13.4496</td> <td>    0.045</td> <td>  296.080</td> <td> 0.000</td> <td>   13.361</td> <td>   13.539</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>years</th>     <td>   -0.7082</td> <td>    0.023</td> <td>  -31.460</td> <td> 0.000</td> <td>   -0.752</td> <td>   -0.664</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Omnibus:</th>       <td>56.254</td> <th>  Durbin-Watson:     </th> <td>   1.847</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Omnibus):</th> <td> 0.000</td> <th>  Jarque-Bera (JB):  </th> <td> 128.992</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Skew:</th>          <td> 0.252</td> <th>  Prob(JB):          </th> <td>9.76e-29</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Kurtosis:</th>      <td> 4.497</td> <th>  Cond. No.          </th> <td>    4.71</td>\n",
       "</tr>\n",
       "</table><br/><br/>Warnings:<br/>[1] Standard Errors assume that the covariance matrix of the errors is correctly specified."
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                            OLS Regression Results                            \n",
       "==============================================================================\n",
       "Dep. Variable:                    ppg   R-squared:                       0.444\n",
       "Model:                            OLS   Adj. R-squared:                  0.444\n",
       "Method:                 Least Squares   F-statistic:                     989.7\n",
       "Date:                Thu, 24 Jan 2019   Prob (F-statistic):          3.69e-160\n",
       "Time:                        09:23:26   Log-Likelihood:                -1510.1\n",
       "No. Observations:                1241   AIC:                             3024.\n",
       "Df Residuals:                    1239   BIC:                             3035.\n",
       "Df Model:                           1                                         \n",
       "Covariance Type:            nonrobust                                         \n",
       "==============================================================================\n",
       "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
       "------------------------------------------------------------------------------\n",
       "Intercept     13.4496      0.045    296.080      0.000      13.361      13.539\n",
       "years         -0.7082      0.023    -31.460      0.000      -0.752      -0.664\n",
       "==============================================================================\n",
       "Omnibus:                       56.254   Durbin-Watson:                   1.847\n",
       "Prob(Omnibus):                  0.000   Jarque-Bera (JB):              128.992\n",
       "Skew:                           0.252   Prob(JB):                     9.76e-29\n",
       "Kurtosis:                       4.497   Cond. No.                         4.71\n",
       "==============================================================================\n",
       "\n",
       "Warnings:\n",
       "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
       "\"\"\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "low\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>OLS Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>           <td>ppg</td>       <th>  R-squared:         </th> <td>   0.030</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>                   <td>OLS</td>       <th>  Adj. R-squared:    </th> <td>   0.029</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>             <td>Least Squares</td>  <th>  F-statistic:       </th> <td>   35.90</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>             <td>Thu, 24 Jan 2019</td> <th>  Prob (F-statistic):</th> <td>2.76e-09</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                 <td>09:23:26</td>     <th>  Log-Likelihood:    </th> <td> -3091.3</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>No. Observations:</th>      <td>  1179</td>      <th>  AIC:               </th> <td>   6187.</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Residuals:</th>          <td>  1177</td>      <th>  BIC:               </th> <td>   6197.</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Model:</th>              <td>     1</td>      <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>      <td>nonrobust</td>    <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "      <td></td>         <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Intercept</th> <td>    5.3616</td> <td>    0.194</td> <td>   27.671</td> <td> 0.000</td> <td>    4.981</td> <td>    5.742</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>years</th>     <td>    0.5683</td> <td>    0.095</td> <td>    5.991</td> <td> 0.000</td> <td>    0.382</td> <td>    0.754</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Omnibus:</th>       <td>649.338</td> <th>  Durbin-Watson:     </th> <td>   1.820</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Omnibus):</th> <td> 0.000</td>  <th>  Jarque-Bera (JB):  </th> <td>6347.614</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Skew:</th>          <td> 2.373</td>  <th>  Prob(JB):          </th> <td>    0.00</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Kurtosis:</th>      <td>13.329</td>  <th>  Cond. No.          </th> <td>    4.85</td>\n",
       "</tr>\n",
       "</table><br/><br/>Warnings:<br/>[1] Standard Errors assume that the covariance matrix of the errors is correctly specified."
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                            OLS Regression Results                            \n",
       "==============================================================================\n",
       "Dep. Variable:                    ppg   R-squared:                       0.030\n",
       "Model:                            OLS   Adj. R-squared:                  0.029\n",
       "Method:                 Least Squares   F-statistic:                     35.90\n",
       "Date:                Thu, 24 Jan 2019   Prob (F-statistic):           2.76e-09\n",
       "Time:                        09:23:26   Log-Likelihood:                -3091.3\n",
       "No. Observations:                1179   AIC:                             6187.\n",
       "Df Residuals:                    1177   BIC:                             6197.\n",
       "Df Model:                           1                                         \n",
       "Covariance Type:            nonrobust                                         \n",
       "==============================================================================\n",
       "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
       "------------------------------------------------------------------------------\n",
       "Intercept      5.3616      0.194     27.671      0.000       4.981       5.742\n",
       "years          0.5683      0.095      5.991      0.000       0.382       0.754\n",
       "==============================================================================\n",
       "Omnibus:                      649.338   Durbin-Watson:                   1.820\n",
       "Prob(Omnibus):                  0.000   Jarque-Bera (JB):             6347.614\n",
       "Skew:                           2.373   Prob(JB):                         0.00\n",
       "Kurtosis:                      13.329   Cond. No.                         4.85\n",
       "==============================================================================\n",
       "\n",
       "Warnings:\n",
       "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
       "\"\"\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "medium\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>OLS Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>           <td>ppg</td>       <th>  R-squared:         </th> <td>   0.050</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>                   <td>OLS</td>       <th>  Adj. R-squared:    </th> <td>   0.049</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>             <td>Least Squares</td>  <th>  F-statistic:       </th> <td>   64.92</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>             <td>Thu, 24 Jan 2019</td> <th>  Prob (F-statistic):</th> <td>1.82e-15</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                 <td>09:23:26</td>     <th>  Log-Likelihood:    </th> <td> -2053.9</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>No. Observations:</th>      <td>  1238</td>      <th>  AIC:               </th> <td>   4112.</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Residuals:</th>          <td>  1236</td>      <th>  BIC:               </th> <td>   4122.</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Model:</th>              <td>     1</td>      <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>      <td>nonrobust</td>    <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "      <td></td>         <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Intercept</th> <td>    8.8791</td> <td>    0.071</td> <td>  125.043</td> <td> 0.000</td> <td>    8.740</td> <td>    9.018</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>years</th>     <td>    0.2832</td> <td>    0.035</td> <td>    8.057</td> <td> 0.000</td> <td>    0.214</td> <td>    0.352</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Omnibus:</th>       <td>133.025</td> <th>  Durbin-Watson:     </th> <td>   1.767</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Omnibus):</th> <td> 0.000</td>  <th>  Jarque-Bera (JB):  </th> <td> 630.863</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Skew:</th>          <td> 0.385</td>  <th>  Prob(JB):          </th> <td>1.02e-137</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Kurtosis:</th>      <td> 6.411</td>  <th>  Cond. No.          </th> <td>    4.73</td> \n",
       "</tr>\n",
       "</table><br/><br/>Warnings:<br/>[1] Standard Errors assume that the covariance matrix of the errors is correctly specified."
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                            OLS Regression Results                            \n",
       "==============================================================================\n",
       "Dep. Variable:                    ppg   R-squared:                       0.050\n",
       "Model:                            OLS   Adj. R-squared:                  0.049\n",
       "Method:                 Least Squares   F-statistic:                     64.92\n",
       "Date:                Thu, 24 Jan 2019   Prob (F-statistic):           1.82e-15\n",
       "Time:                        09:23:26   Log-Likelihood:                -2053.9\n",
       "No. Observations:                1238   AIC:                             4112.\n",
       "Df Residuals:                    1236   BIC:                             4122.\n",
       "Df Model:                           1                                         \n",
       "Covariance Type:            nonrobust                                         \n",
       "==============================================================================\n",
       "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
       "------------------------------------------------------------------------------\n",
       "Intercept      8.8791      0.071    125.043      0.000       8.740       9.018\n",
       "years          0.2832      0.035      8.057      0.000       0.214       0.352\n",
       "==============================================================================\n",
       "Omnibus:                      133.025   Durbin-Watson:                   1.767\n",
       "Prob(Omnibus):                  0.000   Jarque-Bera (JB):              630.863\n",
       "Skew:                           0.385   Prob(JB):                    1.02e-137\n",
       "Kurtosis:                       6.411   Cond. No.                         4.73\n",
       "==============================================================================\n",
       "\n",
       "Warnings:\n",
       "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
       "\"\"\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.display import display\n",
    "\n",
    "for name, daily in dailies.items():\n",
    "    model, results = RunLinearModel(daily)\n",
    "    print(name)\n",
    "    display(results.summary())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's plot the fitted model with the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def PlotFittedValues(model, results, label=''):\n",
    "    \"\"\"Plots original data and fitted values.\n",
    "\n",
    "    model: StatsModel model object\n",
    "    results: StatsModel results object\n",
    "    \"\"\"\n",
    "    years = model.exog[:,1]\n",
    "    values = model.endog\n",
    "    thinkplot.Scatter(years, values, s=15, label=label)\n",
    "    thinkplot.Plot(years, results.fittedvalues, label='model', color='#ff7f00')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following function plots the original data and the fitted curve."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def PlotLinearModel(daily, name):\n",
    "    \"\"\"Plots a linear fit to a sequence of prices, and the residuals.\n",
    "    \n",
    "    daily: DataFrame of daily prices\n",
    "    name: string\n",
    "    \"\"\"\n",
    "    model, results = RunLinearModel(daily)\n",
    "    PlotFittedValues(model, results, label=name)\n",
    "    thinkplot.Config(title='Fitted values',\n",
    "                     xlabel='Years',\n",
    "                     xlim=[-0.1, 3.8],\n",
    "                     ylabel='Price per gram ($)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here are results for the high quality category:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "name = 'high'\n",
    "daily = dailies[name]\n",
    "\n",
    "PlotLinearModel(daily, name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Moving averages\n",
    "\n",
    "As a simple example, I'll show the rolling average of the numbers from 1 to 10."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "array = np.arange(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With a \"window\" of size 3, we get the average of the previous 3 elements, or nan when there are fewer than 3."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# It looks like this doesn't exist in recent versions of Pandas\n",
    "\n",
    "# pd.rolling_mean(array, 3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    NaN\n",
       "1    NaN\n",
       "2    1.0\n",
       "3    2.0\n",
       "4    3.0\n",
       "5    4.0\n",
       "6    5.0\n",
       "7    6.0\n",
       "8    7.0\n",
       "9    8.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# But Series now provides `rolling`\n",
    "\n",
    "series = pd.Series(array)\n",
    "series.rolling(3).mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following function plots the rolling mean."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "def PlotRollingMean(daily, name):\n",
    "    \"\"\"Plots rolling mean.\n",
    "\n",
    "    daily: DataFrame of daily prices\n",
    "    \"\"\"\n",
    "    dates = pd.date_range(daily.index.min(), daily.index.max())\n",
    "    reindexed = daily.reindex(dates)\n",
    "\n",
    "    thinkplot.Scatter(reindexed.ppg, s=15, alpha=0.2, label=name)\n",
    "    roll_mean = reindexed.ppg.rolling(30).mean()\n",
    "    thinkplot.Plot(roll_mean, label='rolling mean', color='#ff7f00')\n",
    "    plt.xticks(rotation=30)\n",
    "    thinkplot.Config(ylabel='price per gram ($)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here's what it looks like for the high quality category."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "PlotRollingMean(daily, name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The exponentially-weighted moving average gives more weight to more recent points."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "def PlotEWMA(daily, name):\n",
    "    \"\"\"Plots rolling mean.\n",
    "\n",
    "    daily: DataFrame of daily prices\n",
    "    \"\"\"\n",
    "    dates = pd.date_range(daily.index.min(), daily.index.max())\n",
    "    reindexed = daily.reindex(dates)\n",
    "\n",
    "    thinkplot.Scatter(reindexed.ppg, s=15, alpha=0.2, label=name)\n",
    "    roll_mean = reindexed.ppg.ewm(30).mean()\n",
    "    thinkplot.Plot(roll_mean, label='EWMA', color='#ff7f00')\n",
    "    plt.xticks(rotation=30)\n",
    "    thinkplot.Config(ylabel='price per gram ($)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "PlotEWMA(daily, name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can use resampling to generate missing values with the right amount of noise."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "def FillMissing(daily, span=30):\n",
    "    \"\"\"Fills missing values with an exponentially weighted moving average.\n",
    "\n",
    "    Resulting DataFrame has new columns 'ewma' and 'resid'.\n",
    "\n",
    "    daily: DataFrame of daily prices\n",
    "    span: window size (sort of) passed to ewma\n",
    "\n",
    "    returns: new DataFrame of daily prices\n",
    "    \"\"\"\n",
    "    dates = pd.date_range(daily.index.min(), daily.index.max())\n",
    "    reindexed = daily.reindex(dates)\n",
    "\n",
    "    ewma = reindexed.ppg.ewm(span=span).mean()\n",
    "\n",
    "    resid = (reindexed.ppg - ewma).dropna()\n",
    "    fake_data = ewma + thinkstats2.Resample(resid, len(reindexed))\n",
    "    reindexed.ppg.fillna(fake_data, inplace=True)\n",
    "\n",
    "    reindexed['ewma'] = ewma\n",
    "    reindexed['resid'] = reindexed.ppg - ewma\n",
    "    return reindexed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "def PlotFilled(daily, name):\n",
    "    \"\"\"Plots the EWMA and filled data.\n",
    "\n",
    "    daily: DataFrame of daily prices\n",
    "    \"\"\"\n",
    "    filled = FillMissing(daily, span=30)\n",
    "    thinkplot.Scatter(filled.ppg, s=15, alpha=0.2, label=name)\n",
    "    thinkplot.Plot(filled.ewma, label='EWMA', color='#ff7f00')\n",
    "    plt.xticks(rotation=30)\n",
    "    thinkplot.Config(ylabel='Price per gram ($)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here's what the EWMA model looks like with missing values filled."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "PlotFilled(daily, name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Serial correlation\n",
    "\n",
    "The following function computes serial correlation with the given lag."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "def SerialCorr(series, lag=1):\n",
    "    xs = series[lag:]\n",
    "    ys = series.shift(lag)[lag:]\n",
    "    corr = thinkstats2.Corr(xs, ys)\n",
    "    return corr"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before computing correlations, we'll fill missing values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "filled_dailies = {}\n",
    "for name, daily in dailies.items():\n",
    "    filled_dailies[name] = FillMissing(daily, span=30)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here are the serial correlations for raw price data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "high 0.49996907065740454\n",
      "low 0.10347947878427055\n",
      "medium 0.16480350777650926\n"
     ]
    }
   ],
   "source": [
    "for name, filled in filled_dailies.items():            \n",
    "    corr = thinkstats2.SerialCorr(filled.ppg, lag=1)\n",
    "    print(name, corr)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It's not surprising that there are correlations between consecutive days, because there are obvious trends in the data.\n",
    "\n",
    "It is more interested to see whether there are still correlations after we subtract away the trends."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "high -0.01114435364441681\n",
      "low 0.03606481939196412\n",
      "medium -0.016501348397930337\n"
     ]
    }
   ],
   "source": [
    "for name, filled in filled_dailies.items():            \n",
    "    corr = thinkstats2.SerialCorr(filled.resid, lag=1)\n",
    "    print(name, corr)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Even if the correlations between consecutive days are weak, there might be correlations across intervals of one week, one month, or one year."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1\t-0.011\t0.036\t-0.017\t\n",
      "7\t0.0095\t-0.032\t-0.045\t\n",
      "30\t-0.0055\t-0.012\t-0.00056\t\n",
      "365\t0.056\t0.016\t0.016\t\n"
     ]
    }
   ],
   "source": [
    "rows = []\n",
    "for lag in [1, 7, 30, 365]:\n",
    "    print(lag, end='\\t')\n",
    "    for name, filled in filled_dailies.items():            \n",
    "        corr = SerialCorr(filled.resid, lag)\n",
    "        print('%.2g' % corr, end='\\t')\n",
    "    print()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The strongest correlation is a weekly cycle in the medium quality category.\n",
    "\n",
    "## Autocorrelation\n",
    "\n",
    "The autocorrelation function is the serial correlation computed for all lags.\n",
    "\n",
    "We can use it to replicate the results from the previous section."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1, -0.011, 0.0094, -0.0055, 0.054\n"
     ]
    }
   ],
   "source": [
    "import statsmodels.tsa.stattools as smtsa\n",
    "\n",
    "filled = filled_dailies['high']\n",
    "acf = smtsa.acf(filled.resid, nlags=365, unbiased=True)\n",
    "print('%0.2g, %.2g, %0.2g, %0.2g, %0.2g' % \n",
    "      (acf[0], acf[1], acf[7], acf[30], acf[365]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To get a sense of how much autocorrelation we should expect by chance, we can resample the data (which eliminates any actual autocorrelation) and compute the ACF."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "def SimulateAutocorrelation(daily, iters=1001, nlags=40):\n",
    "    \"\"\"Resample residuals, compute autocorrelation, and plot percentiles.\n",
    "\n",
    "    daily: DataFrame\n",
    "    iters: number of simulations to run\n",
    "    nlags: maximum lags to compute autocorrelation\n",
    "    \"\"\"\n",
    "    # run simulations\n",
    "    t = []\n",
    "    for _ in range(iters):\n",
    "        filled = FillMissing(daily, span=30)\n",
    "        resid = thinkstats2.Resample(filled.resid)\n",
    "        acf = smtsa.acf(resid, nlags=nlags, unbiased=True)[1:]\n",
    "        t.append(np.abs(acf))\n",
    "\n",
    "    high = thinkstats2.PercentileRows(t, [97.5])[0]\n",
    "    low = -high\n",
    "    lags = range(1, nlags+1)\n",
    "    thinkplot.FillBetween(lags, low, high, alpha=0.2, color='gray')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following function plots the actual autocorrelation for lags up to 40 days.\n",
    "\n",
    "The flag `add_weekly` indicates whether we should add a simulated weekly cycle."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "def PlotAutoCorrelation(dailies, nlags=40, add_weekly=False):\n",
    "    \"\"\"Plots autocorrelation functions.\n",
    "\n",
    "    dailies: map from category name to DataFrame of daily prices\n",
    "    nlags: number of lags to compute\n",
    "    add_weekly: boolean, whether to add a simulated weekly pattern\n",
    "    \"\"\"\n",
    "    thinkplot.PrePlot(3)\n",
    "    daily = dailies['high']\n",
    "    SimulateAutocorrelation(daily)\n",
    "\n",
    "    for name, daily in dailies.items():\n",
    "\n",
    "        if add_weekly:\n",
    "            daily = AddWeeklySeasonality(daily)\n",
    "\n",
    "        filled = FillMissing(daily, span=30)\n",
    "\n",
    "        acf = smtsa.acf(filled.resid, nlags=nlags, unbiased=True)\n",
    "        lags = np.arange(len(acf))\n",
    "        thinkplot.Plot(lags[1:], acf[1:], label=name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To show what a strong weekly cycle would look like, we have the option of adding a price increase of 1-2 dollars on Friday and Saturdays."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "def AddWeeklySeasonality(daily):\n",
    "    \"\"\"Adds a weekly pattern.\n",
    "\n",
    "    daily: DataFrame of daily prices\n",
    "\n",
    "    returns: new DataFrame of daily prices\n",
    "    \"\"\"\n",
    "    fri_or_sat = (daily.index.dayofweek==4) | (daily.index.dayofweek==5)\n",
    "    fake = daily.copy()\n",
    "    fake.loc[fri_or_sat, 'ppg'] += np.random.uniform(0, 2, fri_or_sat.sum())\n",
    "    return fake"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here's what the real ACFs look like.  The gray regions indicate the levels we expect by chance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "axis = [0, 41, -0.2, 0.2]\n",
    "\n",
    "PlotAutoCorrelation(dailies, add_weekly=False)\n",
    "thinkplot.Config(axis=axis, \n",
    "                     loc='lower right',\n",
    "                     ylabel='correlation',\n",
    "                     xlabel='lag (day)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here's what it would look like if there were a weekly cycle."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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RkU2rqMTIqKlbB9qyaphW4KZyraqFCCkAgO2dv0AiPm+FRQBHuZ8XAGw0co/+vWODfsVtPg7xPZMOcMTQ0wyY5J5uJBCmswqms+5FlkrJnDPpYBLDC68tBtHAyYXpSJXs8UOjF6BXYxFDo2fCsvduBOxaH6tqJUZGLd0+0MSwWm0Fq9LpiTxkWUSjFyUG3QlvmdXGwRTYh8EoiOEZAGeI6CQRKQA+CuDRId/7OIAPENGEJzp/wHvuDQPdMNHuuqs/QRBQ8laXPvhU0tIBJoZak0sjSSImMwomMx4xKBKklPu5q+sddHt7ny8fNfg00sP3HYu8thcCdDxiYAwRMXrUiKaRXGKoxv5eU7MCURo4eLUMvIbnR+p1LfoZ13U7GE5kWXZw7Y4bdk0MjDELwC/DvaFfAPB5xth5IvokEX0IAIjo7US0COCnAfwxEZ333lsD8JtwyeUZAJ/0nnvDgJ/nPFXMbqgmjaeSDuoKpbbOCc+yiFJGCoiBiJArhivN22sHK2pgjEXabD98f5wYwojh5ogE6HjEAOwtMUT8/d4chuoWqaSDpjFE9AUvUo9HDJrlYILTUca1+lkaxS9hjD0G4LHYc7/OPX4Gbpqo33s/A+Azo9iPg4hKbEBPHPlsCtm0ik5Ph2FaqDe7kTTFQUG92QkiBlkSMZmWkVNEyCLBtBlS6RRIksAsC4sr6zhzfO4O7/HwuH67GlTB5jIq7j4xG3mdF6BvjCBi6OoWWtrGSuda2wD26GuLRww900Y3Nra0qVm4b/7gtt7u1zxvvbfxey5MFrHsVenXGt0I8Y8LksrnO4z4gJ5+GIdmelUuYnBTSbLbeybN6wwH05n0LG9Tvffohqjv6KGJwGWxUm5AN3a3sl9t9k9f7KUAvRprtx2PFgCXGCYKmeCzNlq9AzWgKF7cxhhDQ9v4OdOFMGIYNMP8oCMhhjuMSj08seKOJB++nxo4uLUMlWYXguSSgCJLKKTcYNVPJ6UVToA+YM6kfjZVHoosBSvQUQztKQ8ghr2sZeDF59nJ/AbhGQBaugVBoEg/oYNUlBnXGHqmA8PemLqV06EOOK61DAkx3GHwqaTBEQNXy7B2MImBv5mVUhIEr9V2IEAf0Iih1dFw8ZprUyUAb7n3aN/tjvE6wy7TSavNUF+YyHL2yT0iBsO0glw6wV3AxIVnAHAY0DFsTE8cvJ5JlmWjXOOsqlN5rHPRgiKGt0omK8HjcbWsJsRwhxEpbuujMQDAYb799gGtZVjncuJTufDCCp1JMiRPg1itNA9MCuKFVxcDi+OpY7NBzUIcvDNpt5ZVXni+93CYZtyriGGtxtup85AkMVLDIAphOdJBtayu1kKr6tREDoosRfSFY6VU8DmZKIK8yv1xFZ8TYrjD4DWGgamkMZjL0DJCj/2hYnjz9IlBEAiZgvv5GYCltYPRafW5TdxIPKIC9O6cSbxV9d5D4ep8fY+qnyNdVafzsByG9V74txaKavC4qVmYjTiTDoZlNaovuGTLE8NERsZUJkyFip69OiGGBCMHYyxiV40Xt/mIj/g8aJZVxhg0Fq4qF6bCfjNpWURadk/DdEqBoLjRxOLK/icG16YadnTppy/4GGWXVb4dxj2H8v4AvD0rcuMjhrmpAupdM1hdF1Oh7RjwLatcW4wD0i+JT9H6CzFeeC6lJMxk3XNTlkRIaTe6TYghwcjR7upBykRVZGRSSt/t8tlU8JpumFgf8cCXvUaro4G8G74oEuYK0XRLkE5SQwH61gHQGa7cLAejLgu5NE4dG9yqZX66AFVxP2ezvfOhPW3NQld3baKKJGAqp6DoObv2qshtNTa8ptINU1bTWRkFNXS9NzUrkhI9KKmkqPDsDsiqcxFDKS0FlfqKLEL0BOj1ZjcYzDROSIjhDiI+oIeoX+sotwDsIKeTVmrtwJEki2LgSPIxFSEGT4A+ADOSeZvqW+87OvD4Ae4xHMXQnjVOeJ4tqCAiTGQ5MXQPdIZIV9WpqFV1KqNEjmdLtyJzGaoHpJYhPqDHdlikVqSYljHtfc9EhHQ+THsexPbiWyEhhjuI8iZdVeOID+05SFishuF2SkDgSPIx4VtWVZnrsrr/U0mRNhibpJF8RHSGHaaTVhuhvjBbcKOrqDNp9BHDSkxjiBBDVo4QQ1OLupLK9faBSH3GaxiamhWky/KqCEkgTGZk+Dq7kg5bxY/jXIaEGO4g+NXUVsRwKKYzHCQsN8IVVV7ZuKoOity4VNJSuQHrdRpyvxM0Wj1cubkGwLU3vvmevoX9EZw4wukMOxSgeavqXNEl0UkuYhi1M8lttx2rYeBSSVMZGVlFDG6YXdOGokhB2swwrX3fT8iybKxxUdGhmULERVdMuZ9F9MgBiAnQYzj7OSGGO4hoDcPmbS74VNJBa6ZXaUdrGOLwLzZRFJDOZQAiOI6Dler+JcDzV5aCFeXdJ+eRz6Y23R6IzWbYccSwkRj2MpXU6mhBpXZKlQFJhukVfaUkwSMFQo7TGTqGE3HY7XedYY23qpaynlWVE57T4Web5gRo0Regk4ghwSgRncOQ32TLgz2wh199zeTVDa/LooC86vrCU6oCUXUvvt1WCO8leLfNqaPTQ70n3mV1J0N7+FTSnJ9Kyu1dxBDpkTSZjxS2TWXlQFcpqOFEvqZuRfp+7fdmelF9YWOPpCgxeFqZLAYdgcfRmTRWxGBYDq6utfGVV9ZQbe/v8BXYfHJbHPERnwchb+ujbYT7Ol/sXwA22UeAvr2Paxn4NOCgivVy28D5lTZ0yyWAQi6NUt616pqWve1iRcZYRHzul0oadcTAz3meny5EiGE6E/7dfCrmTOJrGWr7u5ahX/O8qFU11HD8iEHhI4YxnOQ2ku6q+wWf/upVPH/DvZmo0gm8++6Nq9P9hO1oDIVcCumUgp5mQNNNNNq94Cazn6FbDnTHIwbmYGGqf8psKqPgRl3jBOgGbq3sX2dSlSf1PsRQ6Rj4q5dX4TBgqanj/Xe7+sKxQ5OoNTpgzMGFSzehCu7KVFEUyLIMWZYhSf0vy5ZmQTNdkknJQnAz3kvxmU/nzcUdSdzf3WBZ3cO2GIwx2LYd/HMcB47jQFVVqOr2r3nequrXDMWtqj58B50sixBVFRAI1fUOLMuCbdsQRRGiKG7qUDsIGCtiOD6dCYjheqWDd989XIgfhx/ix7tkjhK27URyk1tpDESE+ekCri1WAACLKzVkVCm4KBzHiVwkjuNAkiSoqgpFUQbebPYa9a4J06vVsHUdk8X+BNgvYuhX5Ba/IQiCAFVVt32sDMOApmkwDAOiKEKSpMi/rS5svnnaZOzYMcbwjWvrcJj7+EqljbfNSnAsExM5CYbhRrOXb6zi/pPTwf74EAQhIAlZlqEoCkRRjOgLs4VUsI/FtAwit46h6RW5SeJozt1o1XMB5Y4Ox3HAGEOaLLRaLdi2DTINWJYFIkK9o2MinwJjANHOU0mO48A0TRiGAdM0I8e9H9rtNiRJQiaTQTqdhiiKfbeLI+5I0kw7iPIkgZBV3N/DGAMxB3mZ0CTAYQyOIOL2chlra2uR3+kTRPyfj0HnlyAIwb87SS5jRQwnpsML9Hp5eKeAbdswDCP4Z5rhqog/UP0OGn/w4s/52xHRhsf1ZheOlw4q5NJQ5P6HwnEcWJYF0zRRyqkwDAOO4+DCpRuYzG5+8ZumiV7PdQSJohisqPwbjY/4Csxf/TDGIp9ZFMUN34Of0ur3PxGh3NZheheZresbJtT5mOQtqykVjuPgxu0yqtVqsH/+DSkOIoKiKFBVFalUaiAJ+t9Hr9eDbW/uePLJoh9pANG8sk/qjDGYpokLK03cqrUj+3uj3MRcVsShmXAlfXtAQ0THcaDrOnQ9TIfKsozrK72ADOe4NhSSKKCYlrHeNYMit+k+Wk4/GIaBXq8X2Vf+/+uLK9B1AwCDY+uoeg4cgQDS22gZ7rkuOe55AwBrDRsnyYCuayAiLC6XUa/XI+dQ/H8AsCwrcg3y1+GwsCwLzWYTrVYLqqoik8lAVdW+N1n/vFpcqXsOOIZcSsDNtRpM0wRjDNmUiHK5DMZY8B1lyHRz8IxBTKew3tqYEvSvpd1gmPtO/P6Ty22eeRgW40UMM25qxbIsXF6uY7VccXOBfW5o/Enon9D94K++R40rt6rQNB1EQHY6i3K5HBAH4B5ky7Ii+zaRV4J9WdtmqwHbttHtdtHtuhe2JEkQBGEkJ/BmePVmBw5zQAAU5kAcsJLNKwKYY4MxB5KiwLQsGI6DxeVq3wFGPBhjwY202WwGkVIqlYIgCOj1etA0bdPjHMeg78U9RgJWvfQDEUEiG5VKxV3dWg6+faMHO9aueaVrYy4rYmGuFDy3nVoN0zRxc60JwzBARMjLDjRNC256E1klqHqudYxNicE/F3q93pbfyWqlBcbcc07JZgDvtCsoQqQeJSeHx7VjOpiYchcAjDGUa61ggdIP/nk/yuuMMQZN06BpGkRRRDqdBhFFFj7uPwe3V0MjQC4lYKkZLhwyorDhOyqpAiRJAIggZzJoliswTBuKPFyEMiy2e+9JiGEA8ikZ03kFK3ULpuXgZrmFI6X9qTO4qQgGxoBSLhVZHfkrtvgqZ5a7QW6XGOLYzk1yNyi3DYAxMAAKM7CysgJFUYJ/pmlC13UYhgEVNnTbgapIkNJpmJ0OlivNLYkhDp9QO53Ri4KMMdQareD7y2dU6Fp40ztfNaFZ7vETyG1FDQCrHRuYcetRCAQGhnKtA92woCrDXYZ+R1PGGAqyg1qtBiKCLMtIi3aQyqk0ejg9Gx0T6zgukXS73UjaajNYtoMa11aalBQA93OXUlGCV0SCLBBMh8FmQDqbDj5no6Vtmt5ijO2pmcK2bbTb/a+XerMb3HyL+TRURUKrEX4//epuJrzPLosCzLS7GG20ets+T/czRpKIJKJHiOg1IrpMRJ/o87pKRH/uvf40EZ3wnj9BRD0iet7790e73Rc+nXSrvn+dSXwf98liKCK3DQd/e7WHx6710DGjqwWeGA5Kc7L1XrjqLihCsLpvtVqoVqtoNpvQdR2MMZRU93RMqVLQpGy5vP9qGerNkAhKXN+nhu7gUj0k+LfOKsE0s3XdgWYxKLKIuWm/nQLD0jY+X6XNOYJyfn8kBsMwkJFYkHK8vlzBysoKVlZWUKlUUKvVsLq6ivX19aFJAXDHVjLP4V/Kp9Hm1hIT6sZbR467ieqMUMings+5X/t7lblBWX4rD74TcF7Z+Dn98zRopkeE9TFri7FrYiAiEcCnAPwYgPsB/AwR3R/b7BcA1BljpwH8DoDf5l67whh7i/fvF3e7PydmDgYxVLlqyYlCSAyX1y10LYaOyXBlPbqqn5sM89NrB6DVgGEzdD19gTkME5nNV8YF1b2xqIoUeMSX9mGVN08M/rFjjOG5VSMolJpJi7irKGEqHV5ia12XJBdmw3TSIJ0hDsYYqn2IwUcxHaYx/AH2juMEIvtOzpVyrJfXuh7eMIt9iCErh8TQMRkmufN6v05yK0cmKPrEEH5X/SIGRSTkZIIsue4jKZXCejMhhjjeAeAyY+wqY8wA8DkAH45t82EAf+o9/gsAP0J7JLmfmA5PxsV9TAx8iD7FRQx1Lbz4alo0YshnVaieSN3TzH3faqChOzC9thaWpmFigPDsw7/ZpBQ+Yth/Hvg6R+qTXsRwq2Wj7EVHBODhOQVEhLlMeMNe9Yjh8GzY3mRYYmhqdjBmMq0IyCjRfDZvqew3wH4n4NOV05NZNLmVdKkvMYTPtU0ncl7X9umkszj5McbQ5iL1vNz/FjmREl2dAYCcyWC9pfXd7qBiFMRwBMAt7udF77m+2zDGLAANAH7jmJNE9D0iepKIfnDQHyGijxPROSI6Vy6XB+7Miels0J9+tWnAsPZnS9xan1QSYwx1PUy91DQ7stIjIsxO7V5nsByGta4Ny9nbiKNpOLC879/SepHIqB+KXtiuyq7GAERnAewXxFNJpsPwQjlM0ZyZkAOSm8tGiYExtiMBusxFCzOxaAEAihwxNHujMRPw59fEZDHQS7IyQRE3rutyfMRgMExwabb92k+oErGMZ9AxWfA50xJB7vM5AZcYZW+Km5TJ7NtU2U4xCmLo983F7ziDtlkGcIw6c5jdAAAgAElEQVQx9lYAvwrgs0RU6LMtGGOfZoydZYydnZkZ3Pc+pYhBqwCHAUuNvRuQvhvwNxefGFoGA89jlgM0jehXGUkn7YAYGGN4alHD125p+MbtvY04mgYLI4aehmJu835CWZkgCV7xkCxDkCR0ega62v46hvVWNJX0StVEz/L7BxEemApv3JMpAZLXYa5rMrRNhiOzYRX77dXhIoZ++gKPvYgY+NV0phCed/3SSEA0YuiYLKKd7deIoRJJJeW21Bd8TKQEyEHEkI6cE+OAURDDIgB+AvoCgKVB2xCRBKAIoMYY0xljVQBgjD0L4AqAu3e7Q0cnwxvQfkwn6VzHSUEQUPAasMVTR+5z0dXfzC6dSV2LodLzLK9dG11z7yIqPpVka1pkBdkPRISCdzEqsshFDftLaOfzyWomHRGcH5pWIqtMgQizmfAyW+3amJnIBinBVldHs711GmIrYsinxCBSbmmjiQbXquH3LmXCY9dPeAZiEYPpRIihvk9z8NFUUjaiL/ifp9wy8OiLVVxcDcmtpAqQvFogKZ1EDP3wDIAzRHSSiBQAHwXwaGybRwF8zHv8EQBfYYwxIprxxGsQ0V0AzgC4utsdOjYVnsT7UYCuc22oJ/JpCN6Kkhf3fFR7g51Jqzu4YcbJp9zbO2JoGk5Q3GZpPRS30BiAcDXqCtAuYe43BxavMaw4qSD1MJMWcbyw0cse0Rk6NogIh7moYXGIqCFCDNmNxCAKhEKKa2S3y6iBMRa5aTpS2Bepn74AABmZgtRAz2IoFfZ3xNDVDHR6bjQqiQJK+XRER/FddP/fd9fwjcsN/Ol3VtH0GkKmJAoaP5JAaGj7t0X8TrBrYvA0g18G8DiACwA+zxg7T0SfJKIPeZv9CYApIroMN2XkW1rfA+BFInoBrij9i4yxXTfIOcERw+L6/iOGfvoCEBWeg21jz83xGkN1+/n3WowIyt29OaF1m6FruAU6zGGAZSGX7j+6lEcxiBikYJW6to+6czLGgrSBWiqh5Xg3BwBv9QTnOHhiWOu61bNHtilA88Qw1SdiAKI6w27TSfVmL5gfncuo6Njh5yqm+t82BCJkvFU2g1vL4KO6D4mBTyNNT2RBRGibUUfSrbqOZS8dbdoMr66En2MmF37fXSbse5fgdjCSAjfG2GMAHos99+vcYw3AT/d5318C+MtR7AOPI6UURAGwHaDcMtEzbKSV0VYl7gYRV8sA4dlHQ3dgOSzIU/Maw2q1FbSeGBavV8TQjDmSSrn0UPsZRAyyGEQM+ymV1O7qsG0HJAgoHT8WRHunJ+SBK+m8QkhLhJ7FYDoMNc3ZlgDtMIZqJ7zRT2f7X7YuMbgLocYuBWj+O5+ZLgWOKFkgZKXBxzErC+iY7t9mkgxZEmFaNjTdRFczBs41vxPghedBNQyPX4ouvs4vdfGOEy6pz2TctuOMMUBR0dPNffX5doOxarvtQ5YEzBXCA3R7nwnQ/OrJz7vzwnNKDHPtDNFIIp9V3YEpADTDQqszfETkMLZBs2gZTiCcjhJuGsknhl6kEGwzFFQuYvA0hnJt/3jga16uXC0Wkcq4xKWKUcE5jn621YU5ToDeImJodC3YXr4qp4oDFzm8AN3YZcTAE8PkTEhiJXXz5m58LUPXigrQ/Ap9P6AcE55NmwXXgkCAIjC8uBjd58vlXtBgbyIdOpPGzbI6lsQAAEe5Vhi3avsrnVTrEzHUOX1hIiVgkiuM4lf5RIT5qTBqWNlGOqlpuO0K4qiMyN4Y/1uBVbW3dQ2Dj5To3mhVRQQJAgRF2VepJF94lrPZwJVyqiT1tW/ymI3oDA6OzBbRE1KoyJO4XO4FJNoPlc7mwrMPvshtt6kkXl/IFsPzLd4KI45szLLqF425v3NnxGDYbE+s1dF5KFm0OCNGThbwynIPvZg5w7QZLpfdc2CCt6ym0xHt8KBjbIlhYSIkhv2mM/QrbuOjgomUgCnuAqyOyJlUHyCQ7YXOEHckDRsxEBGK/gVHBCmdRqPVg268Pr2dtoJP6lImE9wUJre4WQLReoaqZkOUJbQzM+gJKayKE3jlemXgeytcL4rp3ODsb3GPIgY5E676S+rmBJiLFbntdsRnTbPx6JUuHr3SRbOPOWM34FNJrlU1qi+cuxEuurLchLrzS+45kJYIvqNVEEWsjpEz6Q1BDPvNmdRPY4gTwyTnMInrAnzEsLqNiIF3OPEr2L3QGZq6A9MOHUmlLWoYeBQUt9umIomQvQro/TIe0rclypl0QAwTQxBDWqJAP3EYcH5VQybjnqMMhC++sDbwvRHhuY8jyUc0lTQ6jQFKeC0N0lF8xNti8MSwk4jhyroFh7k1Pdeao10cxPsk8fqCCIZLXmRABPzkm6eC115dcVvmExGyYkgmlc74OJPGlhjmCqGffL1rod1H2L0TcLtzRvskxYXnCVVAUSX42YmuySI6AO9M2g4x8ARzZkKCp5uioTvQ++WYdgjdZtBst7iNOQy2bgxlVfURWlbDubr7RYCuN3oQUymQ4EY1KYmQloa7jHid4VLNQC4T3nC/t9RDz+h/jvLEMJPfLJU0mojBbZXtft8kCGCi+3sJCLSvQYi2xWCBqAvszF3Gn7P9XHs7BWNsg/jMRwzLdR2+yej0TBoPHcki7y3W2rqNm156usj1UupnNz+oGFtikATCoWIoQO+XQrdOz4DhuTZUWUImJW8QntMSQSCKrER50Xh2cvsRg+UwNLgTdyYtRgqVRqkz+H/HtGxYmivIbVXcxqPICdD+XN39UstQa3aD1IosiQOLvfphjit0W+nYyHL23WbXxJMX+7uTylvUMPjYUOS2Q7JvtjXo3tS9bCkfzNAoqAJEYfNUkioCPk9aDkMpkkraXsRgOSySPqpp/Qc17QT1Zg82Z8dNp+RIxHBpNdzXtx3LgYhw/3yYUntl2X2dd4i19ke2cyQYW2IAgKP7MJ0Ur2Egog3Cs+/6iKSTuHTPXKxf0jAXy7ruBH1K8ooARSTM8Omk7uhWO/4FZlkOLG9WQTE3PDEU+FoG1bOs7qNUkl9fIUviUGkkHzMZEQK5TrO2yaDIUjCLgTGGJ85XoMfETtthqHe3rmEA+hS5aTu7U/Hf9dT0RPB4qzQS4GpEfNQQr2Xwb8bDoKY5kd46lsMiq/rdIF7xzBgLztuu4aDSdO8XqiTgTYfdqOf+Q2H088qyex3PcRGcDnFsahneMMSwXyKGfj2S4vqCD75lc5XbJpNSkPfSEJbtDFU8xBOLL2xPc7+/PMKIwQ//TcuG1dt+xKB4UZPrTCKIqrovUkmMMdT5iEEWtkUMkkCYSonQTQeOA4iyiKmcAom5N/BKU8O3rkbbjNe7Fvx7aSElQt0ibRUpcuvukBi47zo/ERbiDUMMQLQ1hsEEFDx9yXGcbVVA928RM5oFTCU2b71rhY69Vs8Mur29eSELxfvOT8+mAvfZWstEuWXgUDEFx5v2ZjquRXccMNbEEBeg9wOb96t6HkQMvNulHguj5zgBmu9pM/Dvcn9jMiAGMRwkozlBEdNuUek5sGx3f81OGylVjkwpY4zh21eb+OLLNdQ7/ef65hUhmIMtpVL7opahp5swTBtyJgOBCKIgbCuVBABzWQFdb2UqyhLuns8ib7nHr93V8fXLjcAnD2zdIymOiM6wwzYN/Het5sJV8rDEEG+mt1MBOl5zA0Rt3btBvHle24tEHMZQ577zs8fD60wWBZyZCxc4r6x0UcxnYHXdxZ5pOXiluv051fsRY00MMzk5WGG1dXvXTo1RoNaMFrf1E559ZCSC6q1QzFgYPbtNAZq/yPwaCUUMnTIM0ahkp9AsNyS3LNsjhu6GGoavvLaOv3q+gq9eXMe///JtnLvR2kDaBcV1JQEEMZVCrdHd1Ov/eqDe7EFUVVd4lsVAD9oO5jIiup7GJMoiHj45iazThchsdDUTTc3C09fCqIGvYejXbjuO0igiBi7NIqihm2xQV9U4eGeSa1nlaxmGj/yGaSq5U0StquGsiZZmBxrgdE7G8cnoaOB4OkmRRbCWX6DIcKmq49YYiA1jRQzfePYyfu/Pvox/84dfxEuXlkFEWJgIBb5R6Aw3mha+cVvD+Yrh5u23GYVUYxFDP+HZBxENTCdFLKtbzCzQbRb0gBEo7EcExGyrI6hn8EVs03JgdroAYyjmw5vL9aqGJy7Uw32zHHz+2TL+7Om1iHOsoAoQBIIsCZBSKTAwVNfvbL+dWiNMI0mSiFJq8yrgfiiphK73OUkQcHI+j8PTBRRsVyvq9gw8eakRWH0rre1GDBsnuW0XvtAvplKQvagtLRFSQ5JgblPL6nDE0LMYutw562Ndc+CMIPKPVz37+kKjZ4N5370vOvO4bz4TCPzXqxo6uo2so0Oruee0aTk4t2JsGMt70DBWxPDa9RU8de4SLt1YC9oMLJRGozPYDsMzKzqeXtax1LZxvmri76738MVrPbxYNlDt2UORxBLX/mB2MjdQePYxOQJnEr/yKsWcJaPWGfyW3qZlw/QGsE/k3Ztpz7Dx2WfWgm6k/Ed9eamD3/nyIi54ol4gQHPT3O700B5XeHY/iyKJQxW2xVHv2tA9UVgQAEcUcM+JGWTtDkRmo9010NJsfPe6+1mHaZ7HY7eN9BhjwUJDzmSgyC7RDJtGAuKppHjEMFwqKRLhpgRkPFKyGdDUR0EM8apnBtNm6Bg2HNsBEfC2Y/kN78upIo57bf0ZAy6sdDFRSKN56xZs3YBuWjAdhu8s6SMhsDuFsSKGualQKPMPfERn2GEFdNtw8OWbGq41Nl5obZPh1ZqJL9/U8DdXe/jemoG1bn+SsGwn0sLiyGxxoL7gY2pAoVu0lmHzVVj8IuMxw60w65qz69YDYcRgw/CIoZhPgTGGv/xeJUhvpGUBv/ojC3jXXeExa2k2/p9vr+Avv1eGfx/im+nttKXCqFBv9iBnd2ZV9XG9qsE2/e9ARLnn4J4TsyAAebuNds89R5+82IBls6HbYfjYbb+kTs9AT3P/ZrqQC6u709shBq5fkskwVdp+xMCbJSZT4sAF0k6gm1YwA0MgwkQ+jbbhuN8Xc0XyMzNplAbMKL//UGhbvbDSxbFDE2C2jfVr14I23lXNwfnKwdUbxooY5mfCxmT+TYR3Jt3egQC91LbwxA0tUryykBdxLC8hbhDpWQyX6ia+dkvDV25pG1YMK5VmYNebKmaRSSlbEgP/XEN3gmZqfMRQqXeCFsn9EL/IeKhS2LDPYRvnP2wHlsOCz+OmktxjUMqn8d3rLbx4O7yxf+ThGcwVFPyDt0zj579/PigeAoCnr7Xwh08twbQcKLLk9kyS5TvuTKo2u5DSPjFsz5Hk41pVg+3lsDOKgLWugzPHpwEAWbsLXdPhOAzrPQtPX2+i7hEpETA1oKsqj+Iuq5+jjqSwed5UavjuxKIQpkQbmoU/f7mNdcldAJSHtFfzi6BaU8d62wjO/d06k/iU5GQpCxChY7IgwmK2ExGd4+CJ4bXVLk4ddSdKWt0umou3g9derZlYPaDV0GNFDNGIwb0JTWQkZLwbX890Iu2LN4PDGF4qG/jGbR2mE+Y6H55T8K5DKr7vsIoPn8rgB46oOFHc2ESt2nOw2IqeFLdWwgKmhfnipsKzD0WkYMSgw0JXhiKLYctusIHFQ4yxvo4kHjOZ0aSTqr3Qd25rGpjtt19W8OiL1WC77ztZwINHwvTCvfMZ/OqPLESeq7VNXFzpwPJOUSmVuuOppHrHhOAVe6VlcdvCM+BGDMxx51RkFAGWw2CKCo7MFiGAIWe2glGmj79SD6pvS2kJshg9drbDcKFq4jbXS4kvcmvr2y9yC1b0REjlw+OxXRLMye58guWGga5D6Mh5GCRDMyy0e5t3O+bP2XrXwuMvV/D1i3VcWuvh9rqOKzVjV2maSnxqm+nODjEtBsdxkJYFPHB48HzymZwcRG+GxYBUFoLgfj+LF69hQnb3jQF4ekWHdgAtrGNGDCHL19Y7bt98om0XumkWw1OLOi7UwlAwIxN++GgKp0tyoAOIAuFwTsI75lV86FQa711I4RDXLO3SejSU5NsrH50rRYRndROHC99Qj1/9R6a5DdAZuhYL2l3IAiGvbPwbsyMqdOOrp/WWuz8MwDcWTZjePswVFPz9hyY3vDerivjH75jFR8/OIOXlqG3LwbrOwEAeMdzZiIE3m0ylxW0Lz23dRtkTk5llI+19ztWOjbtPuKvOnN2Brrs3To0TMPulkZ5dNfBSxcA3b+tY84wDokAopnjL6vbSSf53LGfSgV04pwiBO25YZGVCU7PhOK7IrsgSuqLfRn3z49g2WbAYa3RNt62KZYMxoNmz8eqahn/7xZt47OUqVpvbb6kfFZ7dHkl+2s2xHTy0kN1AwjyIKBI1XKpoOHE4LAQsaOvB96VZDN9d2R9W+e1grIhBkSVMeOMEHa4n0XYK3So9G0/c6AUXGuB2xnz/sTSm0oPDaYEIc1kRZ+fVwEVR7TmRfCg/wvHIXDEiPE9u4nCZjHRa7e9MGtR+u6ZtLm4Dbj1D+PvtIGTfLiocabVqbnS0LhXR8MRCWST8o7fPDrzoiAgPH8vjf37fEUxkJC/iINgkQkyntl05O2p0nXC/5zfpWTQI1yphv/5p7lisdm3cc3wWACCAIaM3N7w3Tgw9i+Emx1SvcouYAu9M2qZl1ScGKZOF4tWeTO0gZZZVKNCTSBSgyCK6QhoMW+sMfjrTsB20/KpvL/fvo20xfO1iA//Xlxbxf3/1Nr59tTm0PhYRnktZ1Hp2UCXObAdv3ySN5COiMyx3cebYdPDz1RtlvPNQeM9Z6di4WN9bC+vXFzV8Y1HDs4tNaObu01djRQwAMDe9MZ00bKfVtuHgyVta0LCOADwwJeM9R1SoQ6YN0hLhaD5csV3iTohb3KSuhdnSlvqCj+hshv7OpEFpln4Vz4wxVNpmcCGlpWi6aic5XIexoD04YwyNch09IYW2mIXkEcHfe3AK88WtJ1xNZGW890zRdYcAcAR3/rNtO5HOtK8ndMMCk93ziIgwX9j+pK7r1ZAY7uJs1NWeg4Uj4Y1Fq6xuSE3GieFawwR/H1zp2EFfodIunElBxJDNQJWHbyseh2XaQSGfIBBUWYJNIkyStzQR+Od4q2fD8WpX7pvP4N0ncpjMShBFgiCF5HerruOvnq/g9796GytDDOWKt9u+XNHhc05BiWYYBuH4ZCpIUTc1GxPTYRR88UYZ81kR90yEx+ylijGyGow4bIdhtWvjdtvCM7ca245k+2EkxEBEjxDRa0R0mYg+0ed1lYj+3Hv9aSI6wb32a97zrxHRB3e7L/PTvADtOZM4y+rSut53RcwYw7lVIyiLV0TCDyyk8MB0/zm+m+HMRHhh3mpZ6FkMrY4WOCFkSXStqkMSQ0kVgiikY7IgZzk3zVtW+6/C4vrC7XUdv/eV2/g//u4W/vXfXMdnvrWCr19uQOW60uxEZ1jXnSAtJsGBblqoySVIkptyedPhLL7v5NYrMR9nj+eR8m+OggCk3bTZ2h2qgK41upEeSZObRI+DwBPDqekU5r20IwNwWyMcmfXOXebgZCF6jvLN8xzGcHV94w3/Yt1dXfNumu0K0OWAGLJBKmknxHB5NSRwP2IAgK6Y3jKV5J+zDS0khjcvZHGipGCuoODMTBrvOlXCg0eyEev1UsPAf/jabXz9cmPT1A2vx4lqCle4QV4PzGeGut5FIZpO6gkpCN77bq820O7qeHBGDr47hwHfWdJH1l2Ax7ruBIuEYkrasm3KMNj1byAiEcCnAPwYgPsB/AwR3R/b7BcA1BljpwH8DoDf9t57P4CPAngAwCMA/sD7fTsGrzP4K5NCWgoKfwybYa21cVVxvWkH6SMC8J4FNaIXbAeTKTEoTHMYcHXdjKSRFuaKIIpNbdvE+igQRV73Vx5zW2gM/ChPxoCXbrXw+1+7jSVvVWVY7nDzv36xii+dr+DSWg9L6zpeXO5t2+pY4bQJlVmoyZNwIEASBZTSEj7y8PS2CFaRBHz/yTwYGAQiOLIKSNIda6a3vN6DIHpjHAUEvvphoVsObnt2aSLg+JQaWVFea1i4++Rc8HNab0UucL7d9nLHDnry8MVfN5oWdJvtuP12TzPR6uogUYScSkGR3aZ/26lhAFx32nnOgTZTUAOS6QrpTSMG22FY1x0YlgPddGBbNiSRcP+hbLB4IgJkRcLPvnMO/+rHj+HH3zQZtNi3bIa/frGKT39jJXB08WCMoVxvw4KImlTCZ19shv2NCDh7NLvhPYNw33y47aWKjuOezsDAcPlmBQIRvu+QGsxrb5sMX1/URk4O/OJvJjeamdOjiBjeAeAyY+wqY8wA8DkAH45t82EAf+o9/gsAP0LuXeLDAD7HGNMZY9cAXPZ+344xP72xlgGITXSrR4lBsxheKIfPnZmQN9g6t4szpfBCvrJu4SavL8wW0TbDcYWbCc8++BWqfyJMlUI3xHqfKWf+KE/ddHC90sNXXq0HDdni92jbch0sjZ6NVys6fuuLN/GHTy3h1ZXuUMKZLzw3eha+eakBXXBPUEUS8dG3zyAzYE7xZnj3qQLIYRAEAgOBZQp3rP32MreYSJG97SjyZk0LVnXzBQUZRcRsRgjaTNgMmDgyH2x/fbGMn3rrNCYyEn7wdDGSSrrMRQt3T8jBjdtmwJV1c8cjPv3rRc5GC9u2arUdxyvLHbQ1CwwMkkiYycsoeBGPTSJu1gbPRvZXv65w7QAMuHcug5TXsNDfk5bhwHQYMoqIH7q7hP/ph4/gSCm8KV4p9/C7X17Eczej7VYWKx2ssByW1TlY2SIypRzI+63zeRmzm0zIi+PuuXTw3Sw3DBw5HKYDX7tRBuAK92fnuLSh5uCpHZADYwydATNleGKYze4fYjgC4Bb386L3XN9tGGMWgAaAqSHfCwAgoo8T0TkiOlculwfuTL8iNyCaTorrDM+XjeBAZWXCm6a3LyzGsZAP7YyazXCN+5sLc6WhRGEeU30EaEkUIlWlcddOpWuj0jZxraqhzbVuPjGVwv/y/qP4Fx88iv/mrdN48EgWKYkCcY9AECQB1yoaPvOtFfzeV27jhcX2QIug4zi4UjdwtaJhad1AjZt9e98U4a7p4Tur8sgoIhaKMgTv4jPSxS3bf+wVqlxKpriD0+NaNTz+J6bcgj0iwt1c1KCpORC5x/nGUh33zKj4tUeO4e8/FE4PaxtO4I0nuPOm+d9xZd2KtN7eTsQQOpJ2l0b67jXPkWYzlNISBCI8sBBel6saBf2I4gjSSD0rkkYC3O60Ba63F5+KnSso+KUfOoL33VMKFj0908HnzpXxn767hpWmgf/8QgX/7ku30RFdYf2uU/MQBAEZVcSJ6RR+4szGFhibQZUEnJ4J272IuTCNffFGeI86VpDwMEcOtW2Sg+Uw/N5Xb+OTj92ItJPhf5+P2X0UMfT7JuOfeNA2w7zXfZKxTzPGzjLGzs7MzAzcGSWbCZbD5XonWC1ECt24Cujljo2b3MjAh+fC0G83EIhwqhSuPip2ePEuzEUrnvmLz2EMT19r4pnrrYjLYjJmWfU/16B00mrTwH95uY5yywRjgOOF5D/x4CR+8T2HMJ2TMZWV8X0nC/jZd87hN37iOL7/RA6zeRkZVYTMdUNdahj4T99dw797YnHDfl2vavjDb6ziakWHbrr71ekaEOCgZDXw8KGthbzN8NChdJC7FdIZ3KwOXm3uJZpcA8OJHUSTvCPp5FR4MzleCBcQJiMcPbUAwD0PLt3cuAC6wkUL81kRWVnAMe539CyGDuee2o7GsMbpC3433O1GzvWOGYzEZI6DkmeFPjWbgezrDEJ6oDOpprkpJMNyLaqKSLiXG5DDa3HxiW6SQHjkgUn80/ccjhQDvni7g3//pUV860oTPcOCqso4eWoeWVXC8SkVJ6dU/OjxNBbyw0cLPh44HC7MGo4cRB+3lteDehQAOF2S8bYYOTw5JDlcXuthad0AY8ATF+p4/lb43Rk2Q9sT+d0iyN0vaoHREMMigKPczwsAlgZtQ0QSgCKA2pDvHRpt3cKTN1qYuvceiKoKTTeDEnU+lbTUMGDZbirnudWQJI4VpB3rCv1wV1F2B7MwBp0kyFn3JFqYG+xIevZGG3/5vQq+8FwZf/TUUmD5y8oUOFVMJ2yKNxtrpucwhicvreP3vno76BgJuENi/tn7juC9Z0rBjZaHQIS7pxRMeR0l33PPJH7wdDHijqm0TXzhuTJ++/Gb+Opr6/h/v72CP3hyCbd5g79to2i3cEhfRd7u4PihiQ1/azs4lJeDnLmaUnC1Ra+7J5wxFrGqzm1zVWY5DLe49MkJjhgEIpzm0o6TRw8Hj1+7HiUG22GRucenvUghvghZ7DiB9tDW7aAh31ZYq290JE1toxUGAHz3RisoypvJioE1eSKnBOlEm0RcWGz0fX9Nc4J24Y5l4975TERribbG6P+5Tkyl8M9+ZAHvPLHR7OAQcOquWWREG9MZAXlVxA8cSeHIDkgBcN1SPhbXDRyad6vFfZ2Bx6kYOdQ9cthqrO712GLoL54rB+4rfgBXURU2rb/YDkbxW54BcIaIThKRAldMfjS2zaMAPuY9/giArzD36n4UwEc919JJAGcAfHcnO+EwhicuVqFZDjL5HCbvvRdqqRQIXRlFDJqQ2Q7DctPAyxUTHe8Gq4iEt8yMJgzzkZIIxwoSdNPtnZSZncFEIYNMSh4oPF9YCd0cN2s6fvcri3httQsiitYzeDZUXmy/utLGp762hL99qQbLZhBEtwp2Ni/jf3j3HGbzm38+vm9S2wL+3oOT+LVHjuFH7y0FxViAuwr94vlaMMVKkNy/M5GV8BP3lWDXViF4p+spzt+9ExQUATN51xmmqhLaUHFt9fVNJ3VMFqzsHMvGXDG1xTuiWFoP3SgTGWlDD567SlIw31vNZqHk3WP62vW1yIl0sAAAACAASURBVHY3W3Yk5TnPVayfKsrB72joDgpcrnnYqKFca0NQFAiSBEWWIAsU6ZS6FWyH4Znr4bG5dzZMIfZshmOF8Px67ubGiMGw3Zbtfk2BYzl4y9FcZJvojJLBn0uVBPzUwzP4uXfNIae6f/fwZAqnFopICxZE5lY4v2chdIftBMW0FGQjbAeY4LIZcWIHXHI4GyeHW5uTQ5wYDJvhPz69ip5hR1rY7FYX5bFrYvA0g18G8DiACwA+zxg7T0SfJKIPeZv9CYApIroM4FcBfMJ773kAnwfwCoD/CuCXGGM7MvsSgHtmsxCJoCgiBFFA6a6TeH4t7HJ4lNMZLpY1XKqHefc3zyhDtxXeDs6UZGi6+3fU0gSOHJocKDwzxnAjJsx1DQef+dYK/u5CvW8jsfmpPBiAppjD15ZC/USQRKRkASenUjgxqUZu7IOQlcN9MR2GdZ0hq4r4wP0uQfz4myYjPY18zJZSuGs6hfmCAkFrB0Voc1P5YNLcTpFTCBlFgCIAsixBEAhPnK9u+b6ltoXHr/fwcmX7lbFx1DR3vgQAmN0uJovb00z4C/vk9EZSUUXCyaJLFtmMguyc6066GUtHXOEq6U9xFfiA2/PqeCEkHDXDzZMeUmdYrbWDJoGKIm5adNkPr6120fTOy3xKxD2z4Wdtmwz3zYU/X6psrAauaQ40021NYds2VEnAPXPR77qohNbttsm2XG3ffyiLX3vkKH7+Bw/j6OEi4Hi1MZaNh4osMt52p+D3kTIhkfE6A4+7YuSwrg8mB8thEU3Ud19V2ib+/Nnypg0yd4OR/CbG2GOMsbsZY6cYY7/lPffrjLFHvccaY+ynGWOnGWPvYIxd5d77W9777mGMfXGn+0BEuH8uh5980yyyXOh5WyN87ZaGrulEZjNcWLeCEGw2I+JEYbgT5NJaF5/97houl3tbbww3TeT0ut4+AoVDcwOF53rXQss70IoUzu9lDPjShTqeerUWEIr/OxxJxaoyg4ZUgOa5kkSB8LaTBZyYSkGVhaErV4koEjXw8xlSsoAfuruET3zwKP7BW6ZxdELFg0ey+MX3HsZ8SYUiuRfs2kp40z51dAq7hUCEnCwg57XyUFUZzy12IrMb4mCM4bk1Aw3dnai1vsupX+WuFTQptHu9bc2vBtzGeT74NBKPuydkEABREFCcnQpmUFy64aYjapodHHOBgJOFjakPXoQWZAnk3UGHcSbppoVGq+emO4l21Fb8u1y0cPZYHkU1PJc6hoMHFvIQEM49iJtAapodkJhj2XjgcGZDakQUKGKfjesM/bDWc/By3YbNAMO04JgW6hcv4uT08NbUzXB6JjwfWo4U6Aw3l+tBp9o47irJePu8Ek5Q9MghrjksN4ygncxERsJ/+7YwInlluYvzq+G5te+IYT9hJqfgoYIDfd3NYeqmjUrPwRM3NBS83LCcUrwePIBIwNm54YrYdMvBnz29hucX2/iTb65gacg23r21cOXgZAuRnkL8wbzBFdqcmEzhV953BKe4k+56uYtrFQ1dw0Fdc/Bfz9fwH89VYXnWUNt2MJ+X8CvvO4KjU+FAke2cMFs11JNFAe+6q4D/8YeP4GffORe0TQDcDpxXboV51TPHBpsEtoOCSsipIggMakpGT7c2zEbm0TLCIS8AsNzeXcUp349HhR24pIYBYwzX+ziS4sgpAo7k3BtpLq0gM+e2yHjVSyfxovPRvNS3Er+gCkFaRBIIcso9L4ZJJflFX3ImC8UrStyOvtDoWZE06NtP5KPtty2Guck80rZ7I9NNK9JtF3DTo01OX3jzkWgaycdEn8h5EFqGg28v6XCYeyy0robaxYuwNR1TpcGN8raDY1PhLOim5mB6xtUZHMZw+VZl4PtOFmWcnVcj5BAfDXo9tqh480IOP3jadT8REZZbJjq6DZGGn7A3DMaOGADg0FQe61evonV7CYa3itZthotNhkIxDTmjwLYZNMPB/VMKcspwX8PF1V7Q2Mx2GD77zBoMa+sVy/LNZdiGe3ORVSUy14HXF/g00rGpFPIpCf/9D8zjR+/12h8zwDBt3KxpuFTu4WtXmnAYoCoSCAxFq4kP3ZPBfEHpO8pzGEQiht7WE+rKfMuNNOHKrdFGDICrMyiKCJm5jhLdtPGtK9HZyDxWYq2O4z9vB4wxVLkVd17aZrfSthn4zzOKgLlNeizdPem+ls2oSE1OQpAkvHZ9DYbNIs45XmiOwy+ak0UBUkoGaLiIYa3WBoggZzJQPZF4O+6rc5zofGomjemcDEmgoHrdYQBLpZF23EjbMG28uBi24GaMYbEZNluUiUXmK/OYHDCjpB9eKhtB/YjEbJcUdB2lQjqYNbFbSAJFUoSlmVBXG5RO8nGyGLWyLrWjxypODADwY2+axF3TKQiSADDXZZkW0ddUslOMJTH4XUe7q6toXrkS0Q7y+VQQ6hmmhXsmh3cjvLIcXeGstUz87cu1Td/T7uqoN7volsuugCqLkR43/OrnJhcx+LNmBSJ84P5J/Pz3zyOjCHC8LpOmxSB6XvOZjIA5o4yC3Ua53t50lOdWyCvhnGnDZrje3Pymwkc/gqGj3XU/QzatRJr87QYFRYAqSxCYjZQqwTAtdA0H5270F6FXYiNKKz17x9WmHZOh5y0GHNtGKbM9O2D8wt4sMp1Oi5hKCcimZRAJyMzOYHGlgQvlXtCqpaRunhr0i+Yk0a1HkVVlqFqGtVobUioFEgiKLCEjDz/PmjEWSSPxbqBDufDme2HdwVQKEOAuOMotI0gndS2GitcSnzGGB+YyA23jm1lWeVR6Nha5aPGIoMHxFmh8/c8ocJoT2pEOf3c/ATqOk8VwtkvbDO2njDHc4M4f/54gCYR/+I5ZZNO+mQZ45XZ7aPfZMBhLYpiZCKsZqytV/NARJVgJ57i8Z6PeHZplbYdFQmUf377axPnlwSX+fqvtXqWKlBxt1cwLz7rlRFJTx2KNvO6dz+BX3rcQSQulMiredHoKP3wmB5m5F9VqtR25WLZbuUoUCqEA8Pyaie6A+bWmw7Cu+UVxQG2VixYWpkbSzAsIiYHgitG64V7sT11qbOh7ZTtsw+xqhp1HDXXdgekVY5mdLiYL29QXBtQvDMLdkzJEQUAmJSM9PQMIhBeXw/PudEna9Ht1i+bC2Q1SSkZ9ADFcr2r4gyeX8Nt/dwuXVlqBnVqVpW0N5rm01gvaT2SU6CyDB6eVIM3SNhlmTxwL0kkGl06q9uwwjWTbeOsmrSkKCgUOrJ7F0OsTOTLG8CLXzeBYXkKvGZLXdGnExMDrDLYU6Jc3lusbOhLEIRBFWt8ve+dqvWsF30lKFiINKAspCQ8dKwTp4lrTbSQ4Kiv3WBKDJImY8JwjDAzddg/vPari3kkZWVUAEWBqBtYaOuqd4cbvXa9qQbfIYlqMDJX5wrPlgc4Pv0cSs20UKfq3eOH5dl0PIom5goJ0nxYSExkJv/DOGRwqypjISjg5k0JKldDMT6N0+jSkTAartVbQ5RTYmSD1wJQcpNdMx20u2O+Eq/WiHuqri2E+9fQubao88gpBkgQIREgpAojZsGwb9a6Fl2J56krPQb/gYHmnxKA5MDxHktXtBm3dh0W/VMBmWMiJyMqEbEaBIIkonDiOSttLQwqu/XkrHMtLQX5fEAS0Yqd417DxhefK+IMnl3C9qqHaNvHMsgUp5kgaFk9z0cLbjuUjgnFKIjzEdRJQZ2aQl7222qaNFxfdItSLZT0YKiSDbVotLxDFdIaNxLDUtoM28AIBb5qWUeW6qk6POGI4XFSQ9Radug1MTbv1O47jbKoz+OAts/4ihj93jk2okUUsYwyOIGDOs6Dblo1zN1p46tWt/9YwGEtiANyowUe53oZAhIdmFHzwRBqzkgPDS3mc7xMF9MN5btV2/6Esfuqt00F7467h4HPPlvvePBe5Vtsn8tGve5Dw7IeM/VBQRfzsgwX8wLEMUl78qcoS1EIeU/fegzUpj5U2Twzbz6OKAuHtc6FjYqVj43pz442VF6en00JEeD51dHTEIHp+euX/b+/Mw+Qqy0T/e2uv6n3vTieks29kIStbQsIaIIKMzCA6wnB1FHV0wOt6RxG96qiD253HDREVBx1EUJZhDQIhbCEJ2feNpJPe971r+e4f59SpU9XV3dXd1elO8v2ep57uU3VOna9Onfre7909htaQ5wxaJRWe2dUYV3vHrhkU2nwr1R3xfbhDEcWBmk7q2wdeGDR1RwiZK9Jgp9H4PVVau0JWx0C3UyhPoZxztExGpt/Y15ebayVpVuS4UsrKdzqEWfkeq65AyOkiGDbMN++818b3XzgRl28A0NitcGQYZSu8blfKHdvae8JWPgvA8iRJZVNyXNZ34XG7KJ5UgoMIPb0hmrtCnGjq4bCtftnUPO+gWq79vk40J0WUYoet3/L0XGOhE9+gJ7lje7iISFx5jKyCmH9tMD8DQKlNY6jtNHqixAWjJIQ5R3Nr8jJc5AacKHNV+cc3j3OkduT1xM5awWBfEdjL7Ob5nCwsi/2491YNLhiUUuw+FXuP8ycECHicfHBpkaXKHartYsPBvtmc9qqq00uzKbHdAPbGP3bH8+T8gVeWfpeDxSVerp3ipyLHhc8WGRR0+eKa+Qw3hK0o4LQyawG21fb2MSnZG/NkOCJU1xuTjdPpoGJC3y5tIyHLNCcBZHsiVh2d5q4QP99wipf3N6OUivMvzM53W87PnnCsXeQRs8DaA69X84P1J/o1BRqtVyME4zSG1AWDPUx1Ul7qpVYqclzkZnis0i7dPUFCoQjTclL3h83Ic+M2z+d0OdlyspOfb6ji0S11luYLRu8GpZSRe+LPAMRoG5vifbPlvTbLnFdR4KMkSZ8KEWFJidHAyuN24snMpDjHYwn3rcfb48x/i8sHv8YDaQxHW0K0mZ/R7RDmFBj3cV1CS890M8PmZ1C+ofkZMj0OK5kwrIzf1rGG/ucE+2eeX+JngmlmmljgJ2eIfrBknLWCodi2Ikgs1WxPYz9S3x3XQjEZVS29lg3V53YwxVRzpxb5WTMz1jD9uT2NcbHZkYiKa+dZXpzN0lIPEzKNJh7RzFUjsc2mMRSklhSW4XawvNTLddMChNuM8M2IUtZE1l8rz1SZX+i2btZgRLHFZlKKKBVXWK61Plbc67zSPKs6Z7rI9hqRSQAen5eFBZFYC9AIPLu7kV++Xk2DOcE4xMhPsavoR5uDPLK5ll+8VkWtaV8JR+APm2o5kiQvpSNkrMp6Q2Ei4TDh3t4hmZKODpLY1h9uhzAj30OGLzbJBtvbrAJyqeBzCX6J3dfPHGiPm2jyAi7uuKiUf1k9gXA4gs/vQYkDcbnI9TlTEmKhiOItm+aRTFuIkuN1MDPPbd0XJWX5lkDZdKLDqvrrEvoktSUjsTRG9L4MRhS7bNrC7Hy3FUxhb9CTbh8DxPsZ2iMxP8OxU430BAcPALDfqydag1SbYdIifX2Odi2pKODkIxeWcOm0HL54/WwKMkeWVApnsWCwrwgSC3blBlxMMEv0hiOKA7UDaw12M9LshGiJK+fkcV5+LCX+j+/UWmGUtY3t1iSdk+UnK8NHhtvBpeU+FhbHcicaOkJWSKPf46AoSX/fgcjxOsnqbKJh7z56WlotZ1dZ5tD7EttxOYSlpbGbrKojzHumSampO2bLz3ALx0/a/AtpClO1k+1xWBU/XT4frt5O7rq83Lr2AMdbghyp76K9O0yh35jcolExTZ0hntnXwpYkpRiCYcXv3qrpk5fSZE44oVCEUKdxD+Rmpa4xDNW/YGd6rovcrNgx1ccqh3Q8YDWlB0NrcLqdOB2wZmYu//vKicwpC5DtdzE910HAzFAPO1zkpyiAXj3QTINpivO7HXF+t2TMLXBb5leXU8grMPd32OtQOVMKCMl0i6UR9YaV1VPhQGPQyiAOuAxHPEBHV6+VbOZ2OcnOHNr3kQr5GW6reJ9CyM43tOZwOMKRE4Nn69sFw+GmoBX+W5bjwZtQuSCxAVdBhpsbFhbiSUOTHjiLBUOhTWOoT9IYZG5pfM/WgbCbGuwRF2BMnh9cWozHFUtVf3KHcRNU1tpbeebQH3H5C3neYU3mxflZhLq6aD58mPJwK8tLvXEFu4ZLccDJdFvc/La6XrpCkTgzUqHfmZC/kD7/QpRsj1iF3Vw+HzUN7eRnuLlz1QSr1LLT7SIcMcqCnKjrIBiOEA6GONbQTXVLr7EiNq/t/PIM7lxVZpX46ApG+PUb1TTYghFi/gVFsLOTrIDXalM6GK1dIapaYiu+wcyDiQTcDpZPNEw7vW1tHN5/3OphniolGW6CtpIahQUZfGZNOdeenx83gUz0h/D7jXslIg46+8nWtVPb1sv6fbH7+4rZuYN2DnM5hAvLjQ5pAuRm+yGhTeeswtRWu4m1wxq7I3SFIuy3lbmZV+ixfBWJZqR0RcwlYg9bzcyPb/c5GMUBp1Xuo74z1vMjcVFhmDhj2nqq/qChcNYKhqIEH0OiY9heyndfTVe/vQaaOoKcajZ+XE6HMKukrymhMNPN3y2KTYbvHGtje2U7JxO6tvXHew12M9LwVjIlBTFB2NrYQkWOy1pRjZQFRR4ryqU3bJiU7I7nPK9w7FQsn2M0NAa7j8Hp81o/9Gip5X++pBSfL6Zp7T7Rxn0vVvLzV0/F9aLIy/bwvy4u5SMrSpha6OejF5dadaTausM88Hq1VcStqTtCMByrkZSXk5oZKRiO8NDbNdaKb2Ku1zJ7DYUl5RnkNp+k6eAhlIqwZc/QtIalkzMJEMbtFMpyPUwq8NOT5Cff3t5Btunvcoiw/XjrgGGPSin+vLXeMgVNyvNy6fT+7287E7JcuHoMAeckjDvgw2kKBrdTmJmiYIC+fobd9UGrvWyO1xFX5sa+OCxMs+PZjt2cpHyx+yUVweByCIXm99AZjOA0fYcVCYuK1l5lfU6/SwgM494ajLNWMGT4PfjNiaInGKKtI95MMCnPa60WO3rCccllduxRS9OLfP3+wC+YlBlXCfLxbfUcrbJpDCW5yQ4DiIuqGerKMkpJQvntdOJyCMtsJqVT7eG4MhM9rW2WyawwL5OcIZhbUsXjFLJ8Rgy/iNAVJq7AXH62l6lFfjJ9TiOULxyhqTOEUhDuDSFiCPBLZ+UzuzRAa3s3f3h2K/sPnuD2i0qs4mQN7UEefKOazp4QTT0Ry0GaquNZKcXj79Zb95MIrJ03/NLjK+bFqtK/s/vEAHv2pSjLw1eumcT752ZbJpxd9cG4fhoAtc1dVokNhwiVDd0cqO2/FthbR9ssM5nTATcvLhxS1m1usJ1IOIJDRXA6BYephWX5nUOKorNrDCfbQnEVBRYWxZe5sWsMo+FfiGIXDJ0RFxEzNOxIZUO/zYnslGY4UQq6g2GcpoacuFhMrLU2Gpy1gkFE4kLSErubicQ3AOnPnLT7VHyY6kDnu2lhAXlmSeWu3gh7q2MTfn8aQ08wQtUATqZUKbY17KltSH/7y+KAk6m2qJjo1OJxCqeqRte/ECXHG2sq7/L54sIPqzvCOB3CpDwvc4q81kQPMDHbxdRCH0VZbuq6FBGl+NML23l50yH+8MxW2hub+NDyYkuNP9Xcy2/fNnxFwVDEcDz39JKXgsDbcDDej7FufgEziodfk+eC2eVW+9ajJxuoH2LP62j4q72Rz4GmeFNRQ1cYBwqXClvRXi/ubUqqNTR3hnjGlu1/2YxcynKGds8W5/hpP3UKAaJyQATKs9xx39tg2AVDe1BZ92RJwElJIH5qszueRyMiKUqG12n5L51OBxl5xqIgFI5w9GRqfoaeUIRIxDCN5vpd1pwSZbQqqto5awUDQFFu/w5ogLllsR/sniT5DJ29YY7Wx1ZO88oG/oH7PU5WzjAEQDgSoarHuLxOpyOuF7Wd4009lsmhNLuvkylVSvJjGkNtUzuRSHoyIO0sLPIQSCiTUOh3xDnWpo+CfyFKtjfmgHb6fHH9n2s6YquoC8/L4LNrylkzM5fbLizhExcXk2eq6MGIoqotyLZ9J639X3zrAPPKMvjA4ljRvxOtIU429xIMhS3H82ARSXurOnlmd2zSXFaRxaXTkn/vqZIZ8HL+tBJre6haAxga37yCmJltX2OIbtNZGw5H6FDGtXGqkNVH43hjDwcTtAalFH/ZVm8FVxRlublidv+acH8U5WXQVVdHsLMTr4SZkOthcoGPiUPsmep3xWox2VlQ5O7jQxjNHIZEZti0hqhggNTCVnM8YtVfExEmJLEg2DWGoWSoD4WzWzDk25Pc+jqgpxf5cZk3Vk1rL40JWdD7qjutbOTz8r1k+wePI188KROnQ+juCdErHoLiorQgq1+nZTrMSAB+n9uKtAiHI3FZnunC7YyPUgIo9DniOlWlM+M5kSyPWC0nXX6fpQUGwyou27sk4KQk28O15+dz/oQMHA5HXMTHtvea48IH9x2t5VRtC8smZ3H9+YbD0OV109YdNvwMncYEOZApqbq1l4ffifkVphT6uGlRYVqcnEtt5qRNu4YuGMDIjcg2s9lDEcXeRuNeb2zpxOU3PpfH5WCOzXmaqDXsONkRVxbmAxcUDqtjWHRibn3vOMFgmBy/C/8QysNHkYQMaIDJ2a6kxf/qm06PxgDxDuiwZ2h+BhEh1BO7N7MTQk/DEUVLjzYljQi7LTFZZJLRzDv2JSZqDYnZzqkQ8DiZVxawmvO0OwNMKu1/VRWXxJJi/kJ/2LWGmsb0m5PAUHWj1T2dAr5wD60dxmfw+9xMKBrZCnkgjJpJMVNSND+ltjNsCfBcryNpwyV7y9ZD9X3t5y9tOgjAZTNzWTI1B5epmXSF4ES7kw6Hv1/fSUdPmN+9WU1vKFY3/yMrStLSOxxg0axyqxJoZU0zp+r6LzneH0bmf2xFfrg5SHtvhJrGdlyBWI2ky6dnW5E87zX2WH1HOnvDPLE9phleNDV7wLIVAxFdsIW6uuiorgGMe2k4bXXtppRo6YtEwuEIDbaIroJRFgwVBT7rGgbFRdicZo9UNli+uIFobI3NCY6EfKDmnoh1r2fa2v02tnRaGfLp4KwWDIllMZIxpx8/QzAcYX9NbHswM5KdZRVZdJmCodMZYEI/oapKKY432UthjCy2utgWmVTTMHrtLxcXe1g50ceVk/2cqhqdwnnJSMxliGoM9mzn/to0FgecOMVoetTUFcLhiQ/lfXP7e7R39hAMKwJZfnLMDPWmxjbau0M0uvN4dFcHW4+3xUWwhSKK379dY5W+8Lgkrp1kOvD73MyfUWZtbx6GOQmMiTdaTDKiYGd9kMrGTsv563MJpVmuuES1F/caGeVP7WiwmiPl+J1cO2/4me32BVvt4WOsLPewdop/WNE19uqts/LcZCR5j6a2LiIRY5WdneGzottGC6/LQYW5yHO7nPhyjIVhMBRm16HqAY9t7gzR3G52YXRAr5K4zm5x+Qu2ygmPPL+NL/7oKX731zdpbhtaWHMyzmrBUJxv8zH0Y1rpLwv6UG23tQIsynJTPEAd/URmFPuJBA3pHcFB0J1cqNS1B+kyU/czvE4rOWa4lI5iZJIdEaEsw0mOd/TqIyXD64RMr3GNxOGgrtX4AdV0DC4YXA6hKOCks7uXUDiCNzub7AyfFS0WDIV5/d2j7KzvpSukKMv2UpbtpvpUTPC19Sr+e3MdP1xfyXazl8AT2+s5YlZQFYFblxUP2RmbCsviopOOD6uKpiRoDSfaQhzviL1PjtvYZ83MXGvFe6yhm2d3N8Y51G9aVDis8NsoHrfT0r4iSuHs7Uk6oadCvs/J6kk+LprgTaotQGKo6uhqC1HsloiAzc/w80fe4E/Pb+s3E/pYQzcooyiez9QW7Pe3PeM5mohYXd/Gu3tP0tMb4smXt9PSllp3yYEYkWAQkXwReVFEDpp/k8blicjt5j4HReR22/OviMh+EdlmPopHMp5E8rIDVkRHS1tX0i8jMQs6qiXYk9rmlgaGtBIWwNEZU/dPdiY/NrFw3khX2/aQ1dGITErG4dPkeAZj0irIdBOtDtcZVjR09lq9J1yO+MJ5iZRlOGlpNyZxb04Oi2ZP4MoVM6zXX9l5kkNmxI4IrCz3UNxxipxQK26HWJ3batuCPLypln9//gRvH40J4Gvm5jMvRZPjUJk/s8xa6VbXt8XV4BoKBX4nk7JiC5AmFdOcis2FSW7AxbLJsXvplQOxcy2cmJGyWXUgilPQ5lN+r4Dxmfr7/cRHJI2u4zmKvW6SLyfH0nQVihffOsC9P3+BfUdr+xx3zPQ5hoMhS4Oya8RxddDMe/25N/YRjclaMncykyekoaXuCI//MvCSUmoG8JK5HYeI5ANfB1YAy4GvJwiQDyulFpmPvldqBDidDgpsSUkNSfwMkJAFXd1JRKm4ipHzJgzth1Df1IG315gwXE4HxxqDScty25twnDdCMxJASf7pMSVF6ezu5VStIQAdIkwpT2/hvGTkJoSsHrJFzhT5By6nUBpw0GoKBk9WFgtmlrPs/PPIDHhBhEh+ES2mGl+a4cQX6saBIjvczqLMdq5MyO5t7ox9p4smZbJmZmpJXsPB63axcNYEa3vTruPDfq/5hW4rNLfXtlgqz4vdg2tm5fapcOr3OLhhQXrCke0O4MRQ8nQz2sXzklFuS2rsjTj47G2XM2dqLLqsvqmdHzz0Cg89tTkuHyc6J4SDIfxmsECNWRk4GI418RGM30JTaydv7XjPOv6mKxelZfwjFQw3Ar8z//8d8P4k+1wDvKiUalRKNQEvAmtHeN6UKYyrmdSPOcm2AtpX3cmxhm7Lnprlc8bV40mFytoWXCqMN9KDz+tGQdIaPamW2k6VQnuDoubOlBxdI+HwiQZrpTKpNNeKGBpNDD+DGV7p83PcVt+oPzNSlJbmNjrbjO/B6XKQX1KAx+1k1ZKpBIqLcfv91Dd34BRYXOKJU8kLc/xcPTefr6ydxOWzcARPQQAAIABJREFUcq0SKGAkS/794vREIA3E8vPPs/5/Z9eJYTdlyfQ4mJZrmF3sSVdTC2MLpLyAi6WT41fX75tfQJYvPd9xf9WPRwP77340k9vsOB3CVFvhxMZeB3f/4yr+6YZlVuItwGtbj3DPz55n276T9IQiVhkVFY6QY/qpukKKll6j0q+9/4nLIax/66BRGRdDY58zLeaLGgkjFQwlSqkqAPNvMlNQOWD3llWaz0X5jWlG+poM8MsSkY+LyGYR2VxXN3jYV5TiAZLcokzM9ZBthrh19kZ4bnesUuic0sCQe6meqDYynjPCnfi8xk3wznttcT/krt4wtW3GTeAQmDjMxDY7HreTfFNDUqh+BWG6GO36SMnI9josAeT2+6nrjl3TwQTDu/tO0tNiaDhZGT7r2OWLppI5wfhBdXT1UOIMkul20GQTDNEchoDHydp5+XzlmvO4Zm4eq2bk8NFLSocVtjlU5k4rsSaVhpYOjp4cuK3sQMzJdxMJx3pUSChETkb8PXj5zFyrXMjs0gBLzkufGaY4P32mpMGwJwWeLh8DxIetHqztQkS45IIpfPNTa7lgdmwKbGnr4qePvM4PH9lEyJzkS7M9TLCZ/Ko7wjR0xYeptnf28Ormw9Zz166ck7axD3o3i8h6EdmV5HFjiudINqtGf80fVkrNB1aaj4/09yZKqfuVUkuVUkuLior6260PcTWT+nFAi0icE9oeQjocm3G01LY/0k22WRu9vj0YV4bZnthWluMZtABZqtgjk2pH2Zxk70w1YxTzF+xkecSy17ozAnSbbT4z3GKVCO8PQzAY301Opo8qU0U/3Okk15z4g11dHNxthK42tcYEQ2JV1Qyvkytm57FufgGBJN32RgO3yxk3oQwn2S2KzyXkRmL3o5++ps68DDf/snoCH15ezG0XlqRVIxqoKkG6qT+NyW127Iluh+ti9dhys/x86pZLuPPvLyY7I6ZVvHu0iRPVxv05Od/Xp6tbky1Xp8Dn4OV3Dll+0/LiHBbMSI+2ACkIBqXUlUqp85M8ngBqRKQMwPybzEdQCUyybU8ETpnvfdL82wb8AcMHkVbiq6z2fwPOSRKO6nEJ04uHbvuPagwOFIsnxZx49ub18Wak9JUAjotMGkXBkJjiP3Xi6JXCsBNwSVzb06iNvCQwcInx+uYOTlQ3E+zoQEUiZGV46QgqdjcEqe4IU5ibgcJIunpn53HaOntoao35mfJTLKA32sSZk3YP35xU19jO+hfeprOunp6WFkpcySuqFmV5WDgxM205Gdb7DlLkciSEwkbTqO37T/H86/toM7s1Op2OIZVNHynFWW7LEtEVjHCyOT7PYMnciXzjU9dw8cIKAHodHlrau2hu66KiwEtpRmx6ru8KU29zPGc4FS+9fdDavubiWWkV3CM1GD4J3A581/z7RJJ9nge+Y3M4Xw18RURcQK5Sql5E3MA6YP0Ix9OHOCfXAIJhepEft1MI2mKGZ5UEhmwi6OkNWSsUhwhr5hZyYKMRu7yjsoMbF0Twuh0cj3M8py+80R6ZVD2KguFEdbNln87PCZy2iVNEyA+4OGJu95gaw2BmJKsEhlLkuhVOM1ptT4MxIWb4Pfh7OqzyF69tOTKgxjBWzK4oJjPgpb2zh5a2Lg68V8esiv6D+RwOBw6Hg1AophE0tXbyg4deNXwobSfwul1c+7ErTsfwLTIDXnweF929IXqCIdo7e8jKGN4Cad/RWrYfOEVtQxtV9W00NHckrZZckBOwIstOByLC9GI/W03/4sHaLiYlmIwzA17ueP9ynE4Hf9xt3G8na1vI9xqdGnO8DlrMpLZoGROnwM4971kJbQU5GSyzLRjSwUjtF98FrhKRg8BV5jYislREHgBQSjUC/xd4x3x803zOCzwvIjuAbcBJ4FcjHE8fihL6MvS3MvEkZEHD0JLaopysbbEcsiUFWUwt8lvtDnvDih0nO/oktg21ictA2G2371UlL4SWDo5UDt+/4HQ68fv95OTkEAgEcDqHZoopzoxVzgyGQrS2d1McGEQw7D9l/T+zqO/36ncJl02PZai//M6huLIi+UNo6TmaOJ0Ols6daG1v3n0Ch8OBx+MhEAiQlZVFXl4ehYWFlJaWUlpaSnFxMUVFRWRmZtLRHeSHv3+Vhhbjs7ldTj7zoUv7TcIcLUQkTpsfrjnpmdf28oOHXmH9WwfYcbCKuqb2fkvoL54zMenzo4k9bPVQki6BUVZdOMfKticU4qm/bUcplXTBk+0RXnxzv7V99cUzU+4Tkioj0hiUUg1An6WGUmoz8DHb9oPAgwn7dABLRnL+gRARHA4H2VlucrICtHf2oBBCykVRXhahUIje3l6CwaA1ec4pC1i1YBwS37MhVaJmJICJpbmICMsmZ/L0TsNRuOlYK5PyvFYiXZbPSV4gVk7arg6Gw0OPKppclodDhIhSnKhuZuO7R1m5eGqf/aLnimaEDhV7faQZgwgGl8uFx+OxHi5X39suGAzS3d1NT08Pvb0Dp/bn+V3kZfutxjUn3qtGLcgBp5n8JoLH48Hn8+FwOKhraLbq1AjChTMKebUmfvK4oNhDyeRJ/OXF7bR19tCckCSUaxMMIoLL5cLlcuF0Oq17abjXcqgsnTeJDVuP4nA42Hm4jqKiYpyDTAxut5veUIRf/HkTDS09OBxOBMWd/3DxgBrHaFKcn0lljfF7qWvqGPIC49mNe/nL33YmfS0vO0BJQSalBVmUFmYz7bxiZk8pIRKJEAqFTtt3ZV9sHmvoJhiOJLVCVLWFmVSSy5HKBjyqhx0Hmnhrx3tMnT6J/Y3xZr7Whmbr3s8KeLnkgilpH/foxxeOAZmZmWRlxUwqk8oKOXTccH+0d4eZHIhN+Eopent76e3tZXGFk//Z2Uh7d5CKXBf7j1TT3NpFU1sXLe3dNLd10dzWTWdXL16vm0y/h4yAlwy/0Z83I+Dl4Ht1OM0JamZFGTk5OayZn8n6A+1EFFS1K/Y1gtdrqJTzJucyYcKEpPZBpRTBYJBQKBT3d6CbOjvTx1UXzeL5N/YB8OiL25k/o4y87AButxuv12tN0FHBEA6H4x6hUIiwGbESNUU4HA6cTicOh9EF7URtGx6zrMTShTMoKMi3xhz9KyK43e6UNAK3243b7SYrK4tIJGIJiehY7J852yuUFmbT0t5NOByhpa6B5zbu59brl+Hz+fB645MFD588jsfjIRKJMLU8n9K8DPJaOq0s0gmZTsrNNqiXLZ3G0xv2ADHh6fO6KSkqwO12WwIhGVEBEV1wBIODd0JLFYfDgdfrxev1smpFCQ8/u4OmVqM+zs6DJ1k0e9KAx3f3BPn2L5/l2MkGnE4HLqeDu267gsVzyunqMkpG2L+76N/E54Y79ui9Y/87ubyYXYdrAaE34iI/Pz/u+g10zude38fjL8WEwszJRaxZNp3SwiyK8jPxuo3vKRAIEAjEEl2jGC1bQ3H3fCQSsa6DUsr6fyRCJMfvojjLTW1bkFBY8dBbNSyYmMmc0kBc2ZRjDd1kBrwU5GYQrjcc0H987l3uubMIl0MIK6x7es++49bnuXbVPHKzs6zrnC7OSsGQOMmWFGZbgqGmvpV50yfE7Rv9wfn9AbI73+bYsQa6VDcHthgZsCAkztvdwR4zGaqvHd9tqoSzpk4gIyODjAxYPCWfrceM1dEr++qtMU4vyerXaRRd+XoS6vqEw2FLQNgf0Qn0pisW8O6+SuqaOukNKv76yj6+8vHrkp4nOum73amX/KhtbKOlvduYrDxupp9XMuiKdSg4HA7rBx1FKWX9iMXXg68mTHlJHieqGlFdXby85Sg3XLWM3Ny+Zrm3dxxFRHA6naxaPoeSkhJWqBZePNRIhgtWlGcQ8BuazI1XLuGlTUeImIINoLQwJ26h0R9RoREddyQSiRMSQ9EqnE6nJSztgjzKJRdM5+lXdwCwceuhAQVDbzDE9x54nv1HY3V6PnnrZVy6xMj6tl/n/ki8x6LfRfT/6JiTPfqbsCaVFViv1Ta24fP58PmM7y+6KIpet2AwaC1Wnn9jP4+t32G9z6yKYj7zoUvxug3N2+/3EwgE+vxu7EQXLane99HPb1+kRR/9CbCoAJxbnk3joWZAONwQ5HBDE0/saGZyoZ/zy7OYPzGbU20R3G4X55XlE4o00dkSJKKEJ189wOLLlnO82fBJNrd2Ul/bjMfjwetx84FrVhgJmmnmrBQMiZQWxCp+1jT0X5nyb2/v5/h7p8gV6CMJhojH7WL6eTEV/ZKZhZZgsLdKmFY89HDY6A9uID53x7Xc+9OnANiy5wRv7zjKhQv7mpSGw/4jsQlmVkV6hUJ/2M03JR4P2f52XE4nzU1tNPcY/ppfPfoaX//UurgJtKc3yLZ9sbDO5fMrcDgczJ6Qx3Sz6q094iYrCy5ZMp2NWw5ZzxUMM8TR4XDETXYQE+qJWoXH47EmqlS0rEsWT7MEw1vbj1KQm8mkkjzKS3KZUJyD12NMeKFQmB/+dj07DsTagt5x08VcceHQYt6jC4j+tKXhUFoU82sk/i7ti6KMjNhv5C/rt/Lkq3txu90oBbOnFHP3bavxuJzm4s6f1pVzFPvnt3+f0QVLVPtIJhDfvyKbytZDVDbGmydPNPVyoqmBZ3cZ/jqn04XPI3zytjV8w/ztvrv3BFNmTwVvJihFdW0TEdPUes0lc0dFKMA5IhhKCu2ROskFQzAY5s8vbLG2y4pyKCvKIT8ng/ycDApyY3+zMnz09IZo7+ymvbOXjs4e2jt7aOvspqOzh95gmAsXTokr03z+xBxyA26abf2HnQ5hcuFo1dYp5/IVs/nb24ZJ6YE/b2T+zHIy/MO7kZRS7DtSzcub9vPGtiPW87Nsaf6nC4cIa2cXcri+kxXFXr69ZTsK2HngJK+/e5hLF0+39n137wkrA3xSaR4TimMO5v5CMK9fNT9eMOSmL/Y9OmnYJ5fhMGNyMUV5WdQ1tdHV3cufn98S93pRXhblJbkEQ2F2H4o53j943TLWrV4wonOnixL7gq1+8FLiT728g/96apM14c6dVsa/feI6K4l0LLAvWPqjMMvL12+aS3VLN9uPt7D9eDOHatpJpmhMKcpgwcxyrr9sPv/zqmEqe+7Fd7hw7So6e4I01hi+PafTwfvWjN73eE4IhtJC28qknxvwpbf2WVEo2Zl+7vvCzSnccKlHcjgdwkUzCnh2e2y1PanAjydNiW3JuP39F7F1z3Ga2zppau3k90++xZ23XDak96htbOOVTft59Z0DVCe5dgtnnv5IDzAik4ozDVPBdbYf0W//8gaL55xHwG+8tmnnMeuY5fNTc9LNrChhxuRiDr5nmB8Lck5ftmyqiAg3XL6AXz/2etLX65raqGuKN3PeePlCbr568ekYXkoU5mZYgRJNrZ309AYtTSeRp17ewW//+oa1PR6EwlAQEcpy/ZTl+lm7oJT27hC7Kg0hsbuylU4z7HrJFCOq/8PrlrNl93tU17fS2d5Jzd79RNweOk9VAbB62UzyR/G+PCcEQ9zKJElsf28wFKct3HTlolG54S6ZURgnGKYXj24WZmbAy8duvpT7fvMCAC++sZeVS2bE+ViS0RsM8frWw7y8aX/catNOaWE271u9kNlTS9M+7qFyy7VLeX3rYUsAPvLsZu74u4sJhcJs3hUrMLZiQerRGx+8bhnf+vn/IA4Hy+dXjMKoR851q+Yzb/oEDh+v42RtMydrmjlZ00R1fWufkM2rL5nLR264cNTrOQ0Fl8tJUX6WZUb68g//Qn5OBtmZPrIz/GRl+sjJ9FHf1M6fX9hqHTd7aukZJRSSkelzceH0Ai6cXkAoHOFwrZF7MbvMsG54PW4+8+HL+epP/ooCdu8+ah0rwI1XpKdYXn+cE4KhIDcDp9NBOByhtb2Lru5e/L6YY+rFN/ZaWa45WX6uuWTuqIyjNNfHjNJMDlYbMdvTS0c/Pf/ChVNYPr/CWjn//L9f5Ydf+nurrIQdpRSvv3uY/3ry7T6rTQC/z8Oli6exetksZk1Jb4mEkZDh93LHTRfzo4eM/MhnNuxkzYqZtHX00NFl+B8KcjOYOoRwyEWzJ/HTez6EiFCcP7jjeayYPKGgT5nlYDBMdUMrldVNnKprpiAng8uWzRw335edsqIcSzAcr2rkeNXA9Z9mTSnlq2e4UEjE5XQwq6zvPTZ7ainvW7OQJ1/eHvf8ioVTKS8eeq/tIY1pVN99nCAilORncarOCAOraWilotyYJHqDIR5/8V1r37+78oJ+1dl08KGLzuM3G45RkuPlgslJ21ekFRHhYzdfys6Dp+jq7qWqroVHn9vCh9+3Im6/A8dqePDx1y3ziXU8sGjOJFYvm8XyBRVJBcp44JLF03jxzT3sOniKiFLc/+hGppTHJszl86cMeWK0a5pnEm63k0mleUwqHf37a6SsW72AA8dq4kpP98esKaV87c7r4hZ1Zzu3Xr+MzbuOWXMXwE2jrC3AOSIYwIiAiF7cqrqYYHh+4x6rFV5edoCrR0lbiDKpIMA9N43uORIpyM3kthsu5Jd/2gDAX1/axiWLp1FRXkhtYxv/9dTbvL71UNwxWRk+blizkNXLR9eWmS4MAbiS//39RwmHI+w/Wh0n5IZiRtKcPi6YM4lff+s2Gls6aW3vorWjm7b2blrau2htN/KH2tq7KS7I4kPXLz+nhAIY0Y2f+cfL+befPEEkEmHJ3MlMnzz6CYnnjGCwr/5qzbaX3T1BHl9v0xauumDcrohHylUXz+G1LQfZc7iKiFL89I+vsmjWRJ58ZQchW98Gp9PBusvm84GrFw87gmmsmFSax41rFlrfaTRnIMPvZc448IVokuNxuygtzKa08MzU0EabmRUlfOeuGzn4Xi1rls86Lec8O2fBJCQLjXv+9T20thuxxQW5GVx5UfrqmY83RIQ7P3gZn/veo4RCYY6cqOPIifi+FhctmsY/vm/FGf0D/cDVi9mw5WBcJd2l50/G5To9pbE1mtFgxuQSZkw+faHho5+ZNE4osU121fUtdPcE+YtNW/jAVYvPWm0hSnlxLv+wtm95qmmTivj2v76fz99x1RktFAB8Xjcf/cClcc+N16gijWa8cnbPhDZKErKfn9mwi7YOI828MC+TKy6cPVZDO63cuGYh2/aeYM/hKgpyM/jH961g5ZIZ4zJiZbgsO38yl5rZyxNL8lg8N70liTWas51zRjCU2rKfaxvbeeJv26ztm69efM6YGlwuJ/d++n2crG2mrDAHt/vs+9wiwl0fuYLrV81nQnHuWa8JajTp5pz5xXg9bnKzAjS3dRKJRGg3uzoV52edNofOeMHpdHBeWf5YD2NUERFmVpz+ch0azdnAOeNjgHg/Q5S/v2bJOaMtaDQaTSqcW4KhID67sLQwm8uWzRyj0Wg0Gs345JwSDPZiemBoC6ejZLRGo9GcSYxoVhSRfBF5UUQOmn+T5uCLyHMi0iwiTyc8P0VE3jaPf0RERjWtcYKt/vuEohxWmo1KNBqNRhNjpMvlLwMvKaVmAC+Z28n4D+AjSZ7/HvAj8/gm4KMjHM+ALJtfwZSJhWQGvNz5wcu0tqDRaDRJkJH0chWR/cBqpVSViJQBryilkob4iMhq4PNKqXXmtgB1QKlSKiQiFwH3KqWuGey8S5cuVZs3bx7WmKOf92yK29doNJpUEJEtSqmlg+030iVziVKqCsD8O5TqTgVAs1IqZG5XAuX97SwiHxeRzSKyua6urr/dBiXa4F2j0Wg0yRk0j0FE1gPJKpD92wjPnWx27ld9UUrdD9wPhsYwwnNrNBqNph8GFQxKqSv7e01EakSkzGZKqu1v3yTUA7ki4jK1holA8nZhGo3mnCYYDFJZWUl3d/dYD+WMwOfzMXHiRNzu4fWWGWnm85PA7cB3zb9PpHqgUkqJyMvAzcB/D/V4jUZz7lBZWUlWVhYVFRXaFDwISikaGhqorKxkypTh9SEZqY/hu8BVInIQuMrcRkSWisgD0Z1E5DXgUeAKEakUkaiD+UvA50TkEIbP4dcjHI9GozkL6e7upqCgQAuFFBARCgoKRqRdjUhjUEo1AFckeX4z8DHb9sp+jj8CLB/JGDQazbmBFgqpM9JrpQP5NRqNRhOHFgwajUYzCMeOHeP888/v8/w999zD+vXrBzz23nvv5b777hutoY0K50zZbY1Go0k33/zmN8d6CKOCFgwajeaM4gP/+otRe+/HfnJnv6+Fw2H++Z//mTfeeIPy8nKeeOIJPvnJT7Ju3TpuvvlmnnnmGT73uc9RWFjI4sWLOXLkCE8/bZSH27NnD6tXr+b48ePcddddfPaznx21z5AOtClJo9FoUuDgwYN8+tOfZvfu3eTm5vLYY49Zr3V3d/OJT3yCZ599lo0bN5JYnWHfvn08//zzbNq0iW984xsEg8HTPfwhoQWDRqPRpMCUKVNYtGgRAEuWLOHYsWPWa/v27WPq1KlW3sCtt94ad+z111+P1+ulsLCQ4uJiampqTtu4h4M2JWk0mjOKgcw9o4nX67X+dzqddHV1WduDFSNNPDYUCg2w99ijNQaNRqMZIbNnz+bIkSOWFvHII4+M7YBGiNYYNBqNZoT4/X5+9rOfsXbtWgoLC1m+/MzO2x1RP4axYiT9GDQazZnH3r17mTNnzlgPY0Da29vJzMxEKcWnP/1pZsyYwd133z1m40l2zU5XPwaNRqPRAL/61a9YtGgR8+bNo6WlhU984hNjPaRho01JGo1GkwbuvvvuMdUQ0onWGDQajUYThxYMGo1Go4lDCwaNRqPRxKEFg0aj0Wji0IJBo9FoUiAzM3Osh3Da0IJBo9FoNHGMKFxVRPKBR4AK4BjwD0qppiT7PQdcCGxUSq2zPf9b4DKgxXzqn5RS20YyJo1Gc3bzsQdGL7n1gY8NmvuFUoovfvGLPPvss4gIX/3qV7nlllv41Kc+xdq1a7nhhhu46aabyMvL48EHH+TXv/41R48e5Vvf+taojTvdjFRj+DLwklJqBvCSuZ2M/wA+0s9rX1BKLTIfWihoNJpxzeOPP862bdvYvn0769ev5wtf+AJVVVWsWrWK1157DYCTJ0+yZ88eADZu3MjKlUnb3o9bRioYbgR+Z/7/O+D9yXZSSr0EtI3wXBqNRjPmbNy4kVtvvRWn00lJSQmXXXYZ77zzDitXruS1115jz549zJ07l5KSEqqqqnjzzTe5+OKLx3rYQ2Kkmc8lSqkqAKVUlYgUD+M9vi0i92BqHEqpnhGOSaPRnMWkYu4ZTfqrL1deXk5TUxPPPfccq1atorGxkT/96U9kZmaSlZV1mkc5MgbVGERkvYjsSvK4MQ3n/wowG1gG5ANfGmAcHxeRzSKyObE7kkaj0ZwuVq1axSOPPEI4HKauro4NGzZY1VQvuugifvzjH7Nq1SpWrlzJfffdd8aZkSAFjUEpdWV/r4lIjYiUmdpCGVA7lJNHtQ2gR0R+A3x+gH3vB+4Ho7rqUM6j0Wg06eKmm27izTffZOHChYgI3//+9yktLQVg5cqVvPDCC0yfPp3JkyfT2Nh4RgqGEZXdFpH/ABqUUt8VkS8D+UqpL/az72rg8wlRSVGhIsCPgG6lVH8ObAtddlujObc4E8pujzfGsuz2d4GrROQgcJW5jYgsFZEHbIN5DXgUuEJEKkXkGvOlh0VkJ7ATKATOnHgujUajOUsZkfNZKdUAXJHk+c3Ax2zbSXUppdTlIzm/RqPRaNKPznzWaDQaTRxaMGg0Go0mDi0YNBqNRhOHFgwajUajiUMLBo1GozmNrF69mmi4/XXXXUdzc/MYj6gvIy2JodFoNJph8swzz4z1EJKiBYNGozmj+MWbJ0btve+8aFLS548dO8batWu59NJLeeutt1i4cCF33HEHX//616mtreXhhx9m3rx5fOYzn2Hnzp2EQiHuvfdebrzxRrq6urjjjjvYs2cPc+bMoaury3rfiooKNm/eTHt7O+vWrWPXrl0A3HfffbS3t3PvvfeyevVqLrjgArZs2UJdXR0PPfQQ//7v/87OnTu55ZZbRqWctxYMGo1GkwKHDh3i0Ucf5f7772fZsmX84Q9/YOPGjTz55JN85zvfYe7cuVx++eU8+OCDNDc3s3z5cq688kp++ctfEggE2LFjBzt27GDx4sVDPrfH42HDhg385Cc/4cYbb2TLli3k5+czbdo07r77bgoKCtL6WbVg0Gg0mhSYMmUK8+fPB2DevHlcccUViAjz58/n2LFjVFZW8uSTT3LfffcB0N3dzfHjx9mwYQOf/exnAViwYAELFiwY8rlvuOEGAObPn8+8efMoKysDYOrUqZw4cUILBo1Gc27Tn7lntPF6vdb/DofD2nY4HIRCIZxOJ4899hizZs3qc6xRDq5/XC4XkUjE2u7u7k56bvt57edONzoqSaPRaNLANddcw3/+539a/RreffddwCjT/fDDDwOwa9cuduzY0efYkpISamtraWhooKenh6effvr0DTwJWjBoNBpNGvja175GMBhkwYIFnH/++Xzta18D4JOf/CTt7e0sWLCA73//+1bvBjtut5t77rmHFStWsG7dOmbPnn26hx/HiMpujxW67LZGc26hy24PnbEsu63RaDSaswwtGDQajUYThxYMGo3mjOBMNHuPFSO9VlowaDSacY/P56OhoUELhxRQStHQ0IDP5xv2e+g8Bo1GM+6ZOHEilZWV1NXVjfVQzgh8Ph8TJ04c9vFaMGg0mnGP2+1mypQpYz2Mc4YRmZJEJF9EXhSRg+bfvCT7LBKRN0Vkt4jsEJFbbK9NEZG3zeMfERHPSMaj0Wg0mpEzUh/Dl4GXlFIzgJfM7UQ6gduUUvOAtcCPRSTXfO17wI/M45uAj45wPBqNRqMZISMVDDcCvzP//x3w/sQdlFIHlFIHzf9PAbVAkRjFQy4H/jzQ8RqNRqM5vYzUx1CilKoCUEpViUgcMCqEAAAHxElEQVTxQDuLyHLAAxwGCoBmpVS0AlQlUD7AsR8HPm5u9ojIrhGOfbQpBOrHehADMN7HB3qM6UKPMT2M9zGmMr7JqbzRoIJBRNYDpUle+rdUTmB7nzLg98DtSqmIJC832G8smlLqfuB+8702p5LWPZaM9zGO9/GBHmO60GNMD+N9jOkc36CCQSl15QADqRGRMlNbKMMwEyXbLxv4H+CrSqm3zKfrgVwRcZlaw0Tg1JA/gUaj0WjSykh9DE8Ct5v/3w48kbiDGWn0F+AhpdSj0eeVkanyMnDzQMdrNBqN5vQyUsHwXeAqETkIXGVuIyJLReQBc59/AFYB/yQi28zHIvO1LwGfE5FDGD6HX6d43vtHOO7TwXgf43gfH+gxpgs9xvQw3seYtvGdkWW3NRqNRjN66FpJGo1Go4lDCwaNRqPRxHFGCQYRWSsi+0XkkIgky7Iec0TkmIjsNH0p46LNnIg8KCK19tyPVMqZjIMx3isiJ22+qevGeIyTRORlEdlrlnj5V/P5cXEtBxjfuLmOIuITkU0ist0c4zfM58dNeZwBxvhbETmaxFc6ZoiIU0TeFZGnze30XEel1BnxAJwYiXFTMZLktgNzx3pcScZ5DCgc63EkjGkVsBjYZXvu+8CXzf+/DHxvHI7xXuDzY339bOMpAxab/2cBB4C54+VaDjC+cXMdAQEyzf/dwNvAhcCfgA+az/8C+OQ4HONvgZvH+homjPVzwB+Ap83ttFzHM0ljWA4cUkodUUr1Av+NUZJDMwhKqQ1AY8LTg5YzOZ30M8ZxhVKqSim11fy/DdiLka0/Lq7lAOMbNyiDdnPTbT4U46g8zgBjHFeIyETgeuABczttZYbOJMFQDpywbQ9YQmMMUcALIrLFLOMxXokrZwIMWM5kDPkXsyrvg2Nt7rIjIhXABRiryXF3LRPGB+PoOprmj20YCbEvYlgCUi6PczpIHKNSKnodv21exx+JiHcMhwjwY+CLQMTcHlKZoYE4kwTDkEpojCGXKKUWA9cCnxaRVWM9oDOYnwPTgEVAFfCDsR2OgYhkAo8BdymlWsd6PIkkGd+4uo5KqbBSahFGtYPlwJxku53eUSWcPGGMInI+8BVgNrAMyMfIwxoTRGQdUKuU2mJ/Osmuw7qOZ5JgqAQm2bbHZQkNZVSQRSlVi5HxvXxsR9QvNWYZk2gdq6TlTMYSpVSN+QONAL9iHFxLEXFjTLoPK6UeN58eN9cy2fjG43UEUEo1A69g2O9zRSRaomfc/LZtY1xrmuqUUqoH+A1jex0vAW4QkWMYZvXLMTSItFzHM0kwvAPMML3uHuCDGCU5xg0ikiEiWdH/gauB8VoFdtByJmNNdLI1uYkxvpamDffXwF6l1A9tL42La9nf+MbTdRSRIjH7sYiIH7gSwxcybsrj9DPGfTbhLxi2+zG7jkqpryilJiqlKjDmwr8ppT5Muq7jWHvVh+iBvw4j0uIw8G9jPZ4k45uKES21Hdg9XsYI/BHDhBDE0Lw+imGPfAk4aP7NH4dj/D2wE9iBMfmWjfEYL8VQzXcA28zHdePlWg4wvnFzHYEFwLvmWHYB95jPTwU2AYeARwHvOBzj38zruAv4L8zIpbF+AKuJRSWl5TrqkhgajUajieNMMiVpNBqN5jSgBYNGo9Fo4tCCQaPRaDRxaMGg0Wg0mji0YNBoNBpNHFowaM4pRKR98L1Sfq+7ROS2JM9X2KvEpuE8HhHZYEtc0mhGFS0YNJphYE7S/wujsuWoooyikS8Bt4z2uTQa0IJBc44iIpki8pKIbBWjf8aNtte+JiL7zN4KfxSRzyd5i8uBrcosWCYiS8z6/W8Cn7a9V4WIvGaeZ6uIXGw+//uEcz4sIjeIyDyzF8A2s1jbDHOXvwIfHoVLodH0QQsGzblKN3CTMgoergF+IAZLgQ9gVCb9O2BpP8dfAtgLmP0G+KxS6qKE/WqBq8zz3AL8P/P5B4A7AEQkB7gYeAa4E/iJMgq4LcXIAgcj23bZMD+rRjMktGDQnKsI8B0R2QGsxyhPXIJRVuIJpVSXMnoaPNXP8WVAHVgTe65S6lXztd/b9nMDvxKRnRglCuYCmPtOF5Fi4FbgMVP7eBP4PyLyJWCyUqrL3D8M9EZrcWk0o4kWDJpzlQ8DRcASc3VeA/hIXro4GV3m/pjH9Fdb5m7zvRdiaAD2Vou/N8dxB4bGgVLqD8AN5vs/LyKX2/b3Ymg6Gs2oogWD5lwlB6OefVBE1gCTzec3Au8z+/5mYnTISsZeYDpYpZlbRORS8zW7LyAHqFJGyeuPYLSojfJb4C7zPXYDiMhU4IhS6v9hFLxbYD5fANQppYLD/8gaTWpowaA5V3kYWCoimzEm8n0ASql3MCbk7cDjwGagJcnxz2L0qY5yB/BT0/ncZXv+Z8DtIvIWMBPoiL6glKrBEDC/se1/C7DL7B42G3jIfH4Nhg9Coxl1dHVVjSYBEclUSrWLSADYAHxcmb2UE/b7C/BFpdTBYZ4ngFHGebFSKpnwse/7OPAVpdT+4ZxLoxkKWmPQaPpyv7li34rhFO4jFEy+jOGEHjIiciWGlvKfKQgFD/BXLRQ0pwutMWg0Go0mDq0xaDQajSYOLRg0Go1GE4cWDBqNRqOJQwsGjUaj0cShBYNGo9Fo4vj/YPR/Dhk1LaYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "PlotAutoCorrelation(dailies, add_weekly=True)\n",
    "thinkplot.Config(axis=axis,\n",
    "                 loc='lower right',\n",
    "                 xlabel='lag (days)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Prediction\n",
    "\n",
    "The simplest way to generate predictions is to use `statsmodels` to fit a model to the data, then use the `predict` method from the results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "def GenerateSimplePrediction(results, years):\n",
    "    \"\"\"Generates a simple prediction.\n",
    "\n",
    "    results: results object\n",
    "    years: sequence of times (in years) to make predictions for\n",
    "\n",
    "    returns: sequence of predicted values\n",
    "    \"\"\"\n",
    "    n = len(years)\n",
    "    inter = np.ones(n)\n",
    "    d = dict(Intercept=inter, years=years, years2=years**2)\n",
    "    predict_df = pd.DataFrame(d)\n",
    "    predict = results.predict(predict_df)\n",
    "    return predict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "def PlotSimplePrediction(results, years):\n",
    "    predict = GenerateSimplePrediction(results, years)\n",
    "\n",
    "    thinkplot.Scatter(daily.years, daily.ppg, alpha=0.2, label=name)\n",
    "    thinkplot.plot(years, predict, color='#ff7f00')\n",
    "    xlim = years[0]-0.1, years[-1]+0.1\n",
    "    thinkplot.Config(title='Predictions',\n",
    "                 xlabel='Years',\n",
    "                 xlim=xlim,\n",
    "                 ylabel='Price per gram ($)',\n",
    "                 loc='upper right')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here's what the prediction looks like for the high quality category, using the linear model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "name = 'high'\n",
    "daily = dailies[name]\n",
    "\n",
    "_, results = RunLinearModel(daily)\n",
    "years = np.linspace(0, 5, 101)\n",
    "PlotSimplePrediction(results, years)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When we generate predictions, we want to quatify the uncertainty in the prediction.  We can do that by resampling.  The following function fits a model to the data, computes residuals, then resamples from the residuals to general fake datasets.  It fits the same model to each fake dataset and returns a list of results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "def SimulateResults(daily, iters=101, func=RunLinearModel):\n",
    "    \"\"\"Run simulations based on resampling residuals.\n",
    "\n",
    "    daily: DataFrame of daily prices\n",
    "    iters: number of simulations\n",
    "    func: function that fits a model to the data\n",
    "\n",
    "    returns: list of result objects\n",
    "    \"\"\"\n",
    "    _, results = func(daily)\n",
    "    fake = daily.copy()\n",
    "    \n",
    "    result_seq = []\n",
    "    for _ in range(iters):\n",
    "        fake.ppg = results.fittedvalues + thinkstats2.Resample(results.resid)\n",
    "        _, fake_results = func(fake)\n",
    "        result_seq.append(fake_results)\n",
    "\n",
    "    return result_seq"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To generate predictions, we take the list of results fitted to resampled data.  For each model, we use the `predict` method to generate predictions, and return a sequence of predictions.\n",
    "\n",
    "If `add_resid` is true, we add resampled residuals to the predicted values, which generates predictions that include predictive uncertainty (due to random noise) as well as modeling uncertainty (due to random sampling)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "def GeneratePredictions(result_seq, years, add_resid=False):\n",
    "    \"\"\"Generates an array of predicted values from a list of model results.\n",
    "\n",
    "    When add_resid is False, predictions represent sampling error only.\n",
    "\n",
    "    When add_resid is True, they also include residual error (which is\n",
    "    more relevant to prediction).\n",
    "    \n",
    "    result_seq: list of model results\n",
    "    years: sequence of times (in years) to make predictions for\n",
    "    add_resid: boolean, whether to add in resampled residuals\n",
    "\n",
    "    returns: sequence of predictions\n",
    "    \"\"\"\n",
    "    n = len(years)\n",
    "    d = dict(Intercept=np.ones(n), years=years, years2=years**2)\n",
    "    predict_df = pd.DataFrame(d)\n",
    "    \n",
    "    predict_seq = []\n",
    "    for fake_results in result_seq:\n",
    "        predict = fake_results.predict(predict_df)\n",
    "        if add_resid:\n",
    "            predict += thinkstats2.Resample(fake_results.resid, n)\n",
    "        predict_seq.append(predict)\n",
    "\n",
    "    return predict_seq"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To visualize predictions, I show a darker region that quantifies modeling uncertainty and a lighter region that quantifies predictive uncertainty."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "def PlotPredictions(daily, years, iters=101, percent=90, func=RunLinearModel):\n",
    "    \"\"\"Plots predictions.\n",
    "\n",
    "    daily: DataFrame of daily prices\n",
    "    years: sequence of times (in years) to make predictions for\n",
    "    iters: number of simulations\n",
    "    percent: what percentile range to show\n",
    "    func: function that fits a model to the data\n",
    "    \"\"\"\n",
    "    result_seq = SimulateResults(daily, iters=iters, func=func)\n",
    "    p = (100 - percent) / 2\n",
    "    percents = p, 100-p\n",
    "\n",
    "    predict_seq = GeneratePredictions(result_seq, years, add_resid=True)\n",
    "    low, high = thinkstats2.PercentileRows(predict_seq, percents)\n",
    "    thinkplot.FillBetween(years, low, high, alpha=0.3, color='gray')\n",
    "\n",
    "    predict_seq = GeneratePredictions(result_seq, years, add_resid=False)\n",
    "    low, high = thinkstats2.PercentileRows(predict_seq, percents)\n",
    "    thinkplot.FillBetween(years, low, high, alpha=0.5, color='gray')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here are the results for the high quality category."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "years = np.linspace(0, 5, 101)\n",
    "thinkplot.Scatter(daily.years, daily.ppg, alpha=0.1, label=name)\n",
    "PlotPredictions(daily, years)\n",
    "xlim = years[0]-0.1, years[-1]+0.1\n",
    "thinkplot.Config(title='Predictions',\n",
    "                   xlabel='Years',\n",
    "                   xlim=xlim,\n",
    "                   ylabel='Price per gram ($)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "But there is one more source of uncertainty: how much past data should we use to build the model?\n",
    "\n",
    "The following function generates a sequence of models based on different amounts of past data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "def SimulateIntervals(daily, iters=101, func=RunLinearModel):\n",
    "    \"\"\"Run simulations based on different subsets of the data.\n",
    "\n",
    "    daily: DataFrame of daily prices\n",
    "    iters: number of simulations\n",
    "    func: function that fits a model to the data\n",
    "\n",
    "    returns: list of result objects\n",
    "    \"\"\"\n",
    "    result_seq = []\n",
    "    starts = np.linspace(0, len(daily), iters).astype(int)\n",
    "\n",
    "    for start in starts[:-2]:\n",
    "        subset = daily[start:]\n",
    "        _, results = func(subset)\n",
    "        fake = subset.copy()\n",
    "\n",
    "        for _ in range(iters):\n",
    "            fake.ppg = (results.fittedvalues + \n",
    "                        thinkstats2.Resample(results.resid))\n",
    "            _, fake_results = func(fake)\n",
    "            result_seq.append(fake_results)\n",
    "\n",
    "    return result_seq"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And this function plots the results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "def PlotIntervals(daily, years, iters=101, percent=90, func=RunLinearModel):\n",
    "    \"\"\"Plots predictions based on different intervals.\n",
    "\n",
    "    daily: DataFrame of daily prices\n",
    "    years: sequence of times (in years) to make predictions for\n",
    "    iters: number of simulations\n",
    "    percent: what percentile range to show\n",
    "    func: function that fits a model to the data\n",
    "    \"\"\"\n",
    "    result_seq = SimulateIntervals(daily, iters=iters, func=func)\n",
    "    p = (100 - percent) / 2\n",
    "    percents = p, 100-p\n",
    "\n",
    "    predict_seq = GeneratePredictions(result_seq, years, add_resid=True)\n",
    "    low, high = thinkstats2.PercentileRows(predict_seq, percents)\n",
    "    thinkplot.FillBetween(years, low, high, alpha=0.2, color='gray')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here's what the high quality category looks like if we take into account uncertainty about how much past data to use."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "name = 'high'\n",
    "daily = dailies[name]\n",
    "\n",
    "thinkplot.Scatter(daily.years, daily.ppg, alpha=0.1, label=name)\n",
    "PlotIntervals(daily, years)\n",
    "PlotPredictions(daily, years)\n",
    "xlim = years[0]-0.1, years[-1]+0.1\n",
    "thinkplot.Config(title='Predictions',\n",
    "                 xlabel='Years',\n",
    "                 xlim=xlim,\n",
    "                 ylabel='Price per gram ($)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Exercises"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "**Exercise:**   The linear model I used in this chapter has the obvious drawback that it is linear, and there is no reason to expect prices to change linearly over time. We can add flexibility to the model by adding a quadratic term, as we did in Section 11.3.\n",
    "\n",
    "Use a quadratic model to fit the time series of daily prices, and use the model to generate predictions. You will have to write a version of `RunLinearModel` that runs that quadratic model, but after that you should be able to reuse code from the chapter to generate predictions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Solution goes here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Solution goes here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Solution goes here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Solution goes here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Exercise:** Write a definition for a class named `SerialCorrelationTest` that extends `HypothesisTest` from Section 9.2. It should take a series and a lag as data, compute the serial correlation of the series with the given lag, and then compute the p-value of the observed correlation.\n",
    "\n",
    "Use this class to test whether the serial correlation in raw price data is statistically significant. Also test the residuals of the linear model and (if you did the previous exercise), the quadratic model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Solution goes here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Solution goes here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Solution goes here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Solution goes here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Worked example:** There are several ways to extend the EWMA model to generate predictions. One of the simplest is something like this:\n",
    "\n",
    "1. Compute the EWMA of the time series and use the last point as an intercept, `inter`.\n",
    "\n",
    "2. Compute the EWMA of differences between successive elements in the time series and use the last point as a slope, `slope`.\n",
    "\n",
    "3. To predict values at future times, compute `inter + slope * dt`, where `dt` is the difference between the time of the prediction and the time of the last observation.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "name = 'high'\n",
    "daily = dailies[name]\n",
    "\n",
    "filled = FillMissing(daily)\n",
    "diffs = filled.ppg.diff()\n",
    "\n",
    "thinkplot.plot(diffs)\n",
    "plt.xticks(rotation=30)\n",
    "thinkplot.Config(ylabel='Daily change in price per gram ($)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "filled['slope'] = diffs.ewm(span=365).mean()\n",
    "thinkplot.plot(filled.slope[-365:])\n",
    "plt.xticks(rotation=30)\n",
    "thinkplot.Config(ylabel='EWMA of diff ($)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(Timestamp('2014-05-13 00:00:00', freq='D'),\n",
       " 10.92951876545549,\n",
       " -0.00262422491642447)"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# extract the last inter and the mean of the last 30 slopes\n",
    "start = filled.index[-1]\n",
    "inter = filled.ewma[-1]\n",
    "slope = filled.slope[-30:].mean()\n",
    "\n",
    "start, inter, slope"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "# reindex the DataFrame, adding a year to the end\n",
    "dates = pd.date_range(filled.index.min(), \n",
    "                      filled.index.max() + np.timedelta64(365, 'D'))\n",
    "predicted = filled.reindex(dates)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "# generate predicted values and add them to the end\n",
    "predicted['date'] = predicted.index\n",
    "one_day = np.timedelta64(1, 'D')\n",
    "predicted['days'] = (predicted.date - start) / one_day\n",
    "predict = inter + slope * predicted.days\n",
    "predicted.ewma.fillna(predict, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the actual values and predictions\n",
    "thinkplot.Scatter(daily.ppg, alpha=0.1, label=name)\n",
    "thinkplot.Plot(predicted.ewma, color='#ff7f00')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As an exercise, run this analysis again for the other quality categories."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
